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First Images from EXPLORER Total-Body Positron Emission Tomography Scanner

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An amazing new PET/CT scanner has produced its first images of human subjects, giving scientists and clinicians new opportunities to treat cancer and other diseases. The EXPLORER is a high sensitivity total-body positron emission tomography scanner developed by a collaboration of many different scientists. It is capable of imaging the entire human body in less than a second and with excellent fidelity.

It was originally conceived by Simon Cherry and Ramsey Badawi, two scientists at UC Davis, but years of engineering and scientific work was required to turn it into reality. The first model was eventually built by United Imaging Healthcare out of Shanghai, China, and the company is working toward commercializing it and bringing it to clinics and research laboratories. The scanner’s first work has been conducted at the Department of Nuclear Medicine at the Zhongshan Hospital in Shanghai.

Because of the scanner’s high efficiency, it is able to produce images in as little as a second using a standard radiation dose, much faster than with conventional devices. Moreover, to help reduce radiation exposure, the dose can be reduced at the expense of just a few extra seconds of the scanner’s time. And if optimal image quality is key, a longer scan at a standard dose will provide impressive results.

The developers of the device believe that new whole-body studies, which can assess how different tissues and organs react to different stimuli, will be able to be performed. The spread of inflammation, the impact of different disorders, and the mobility of cancer tumors should also be subject to easier assessment using the new scanning technology.

The researchers will be presenting the first scans of people using the system at the upcoming RSNA conference in Chicago.

Here’s a scan of a whole body taken using the EXPLORER:

Video of an injected radiotracer moving through the body:

Project page: EXPLORER…

Via: UC Davis…


Siemens Healthineers Unveils MAGNETOM Altea 1.5 Tesla MRI Scanner

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Siemens Healthineers has unveiled a new 1.5 Tesla MRI scanner, the MAGNETOM Altea, at the RSNA conference in Chicago.

The device features a generous 70 centimeter bore that will fit some of the largest patients, as well as the company’s BioMatrix technology that helps to prepare for scans based on patient info and speeds up the workflow. In part, this is done using a tool that alleviates the need for placing anatomical landmarks on the patient skin, instead using the skin itself as the marker.

A few dozen “acceleration packages” are provided with the scanner that essentially automate often-performed and repeat scans.

For clinics wishing to help children and claustrophobic patients get through scans, an optional in-bore infotainment system that delivers sound and video, can be purchased separately.

Here’s a promo video for the MAGNETOM Altea and Lumina, a related 3.0 Tesla scanner:

Product page: MAGNETOM Altea…

Via: Siemens Healthineers…

Nanome Looking for VR Folks to Help Complete Human Biome Map

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Molecular scientists these days have tools at their disposal that allow  to do quite incredible things. To use these tools to create new drugs and therapies, they need new ways to visualize and manipulate molecules using computers.

Proteins are important subjects of study, as an understanding of their structure and how they fold and work can lead to the design of appropriate drugs for a variety of conditions. They’re typically large molecules with a lot of complexity and using conventional software and 2D computer screens has its limitations. But, a great deal of this complexity can be analyzed and resolved by regular people with just a bit of knowledge about proteins and a virtual reality headset.

Nanome, a company based in San Diego, California, has released a virtual reality app that they dub an “immersive virtual lab” that “makes it possible for anyone with a VR rig to contribute” to the creation of a complete map of the Human Proteome.

If you have a virtual reality headset, such as the Oculus, Nanome is looking for your help. And if you don’t yet have one, perhaps this may be a starting point if you’re looking for something other than games to play with.

More from Nanome: Collaborative Structure Based Drug Design in Virtual Reality…

More about the Nanome app…

Link: Nanome.ai…

Siemens Healthineers Releases Mobilett Elara Max X-Ray

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Siemens Healthineers is releasing a new mobile, general purpose X-ray system, the Mobilett Elara Max. It features secure connectivity to the hospital’s IT systems to quickly store and retrieve the captured images, a design to make the unit easier to clean, and overall improved ergonomics for ease of use.

The cabling has been integrated into the unit, so wiping it with disinfectants is easy. Joints of the X-ray arm have parts positioned closer together to narrow the size of crevices and reduce tolerances.

Basically, this is a light and mobile budget friendly device that can probably integrate into the clinic’s IT system fairly easily. Siemens Healthineers does offer additional software options to boost the capability of the system and the clinic’s ability to process related data.

“When we developed the Mobilett Elara Max, patient safety was of primary importance to us,” said Carsten Bertram, Head of X-Ray Products at Siemens Healthineers, in a published statement. “And because protecting patient data is also becoming more important, we equipped the system with comprehensive IT security technology.”

Via: Siemens Healthineers…

Self Forming Injectable Gel for Cervical Brachytherapy Procedures

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A Virginia Tech polymer chemist and a University of Virginia clinical oncologist, have teamed up to create a special gel to reduce the pain associated with cervical cancer brachytherapy. This kind of therapy involves placing radioactive sources near the location of tumors, which essentially kill the cancer cells. Gauze is placed within the vagina to help with bleeding and other side effects, and it along with the cells dying from the therapy generates pain.

The new gel is made to replace the gauze with something more pleasant, and biocompatible gels can be very smooth, soft, and conforming. The new gel from he researchers in Virginia is made mostly of baking soda and a digestive aid, and it is actually “manufactured” once the ingredients are injected into the body. The ingredients, along with the body’s moisture, combine in a “click” reaction that quickly forms bonds that produce the gel form of the material.

It is hoped that the gel will be delivered before brachytherapy to isolate the tumors and soothe the nearby tissues during and post the procedure. So far, it has been tried in human cadavers and pre-clinical studies will be the next step before women with cervical cancer can safely try it during their treatments.

Via: Virginia Tech…

Attilan Developing Virtual Prosthetic Arm Training

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Upper body amputees that receive powered prosthetic arms and hands require a lot of practice to get used to new prostheses. These devices are not exactly intuitive to use, so peg boards and other rehab gadgets are employed. This kind of rehab can get pretty monotonous and, because the prostheses are often heavy, physically exhausting.

Attilan, a European affiliate of Motorica, a Russian company, is advancing the process of getting used to a prostheses into the virtual world, and in the process making it easier and more fun.

Attilan is developing games like firing a laser bow and arrow while walking through hallways, all designed to replicate how a powered prosthetic arm would perform in the same real situation. After regularly playing such games, the patient would probably have improved hand-eye coordination and other neuro-motor skills.

The latest prototype was just presented at the  Russian-British Business Forum (RBBF) in London.

Here’s a video of what Attilan is hoping to achieve in the near future:

 

Link: Attilan…

New E-Skin Nearly as Sensitive as Real One

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At Stanford University researchers have created an electronic skin that is sensitive enough to give robotic hands the ability to handle delicate berries. Though mostly intended for robotic hands, the technology may give powered prostheses similar capabilities.

The e-skin can measure slight pressures and even the direction in which they’re applied, which gives enough information to a pair of robotic fingers to manipulate soft and even squishy objects without damaging them. It also can measure the temperature and has other sensors built-in that can help an artificial hand be more like the real one.

“This technology puts us on a path to one day giving robots the sort of sensing capabilities found in human skin,” said Zhenan Bao, the lead researcher on the project.

The finger tips of the e-skin have bumps, just like ours that make fingerprints, and these are what give the e-skin the ability to sense direction as they move as they’re pushed.

Here’s a short video showing off the technology:

Study in Science Robotics: A hierarchically patterned, bioinspired e-skin able to detect the direction of applied pressure for robotics…

Via: Stanford…

Amazon Comprehend Medical Understands Free-Form Clinical Text

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Amazon, not content with disrupting retail, distribution, computing, publishing, grocery shopping, and other spheres of business, is now turning its attention to medicine. It has recently announced the launch of its own brand of consumer medical devices, and has now released a service that can convert unstructured medical data, such as doctor’s notes, into tagged and searchable information.

The new Amazon Comprehend Medical offering is able to elucidate things like diagnoses, drugs and dosages prescribed, results of examinations, and related info from free-formed text. It seems to aim to make forms irrelevant, letting medical professionals focus on the natural flow of an exam or office visit instead of on the form, which has to be filled out in a specific fashion.

The machine-learning system should be able to improve over time as it continues to learn from new inputs and an increased variety of data. This will probably have to involve industry partners that sign up to use its capabilities within their products, and therefore will help to train the system for their specific use cases.

Amazon describes the system as being “HIPAA-eligible,” which we take to mean that it can be made HIPAA-compliant if desired, which it certainly will in most cases.

Link: Amazon Comprehend Medical…

Via Amazon’s AWS Machine Learning Blog…


electroCore Vagus Nerve Stimulator Cleared for Prevention of Cluster Headache

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electroCore, based out of Basking Ridge, New Jersey, received the first FDA clearance for a product to prevent cluster headache. The gammaCore non-invasive vagus nerve stimulation (nVNS) system was previously cleared for treating pain that has already kicked in, that is related to migraines and episodic cluster headaches. The new clearance means that doctors can prescribe it for prevention as well.

The latest version of the device, called gammaCore Sapphire, has a couple electrodes that are placed on the neck over the location of the vagus nerve. The device sends electric current through the skin to the nerve, and toward the brain, disrupting processes that cause certain types of pain.

The device, about the size of a smartphone, is small enough to be carried around, and therapy can be administered at will and as needed. There doesn’t seem to be any known serious side effects from this kind of therapy, so it seems to be safe for repeated and regular use, as long as it’s used by adults.

Here’s some data from the studies that led to this latest clearance, according to electroCore:

This clearance was supported by results from two studies, including from the PREVA (PREVention and Acute treatment of chronic cluster headache) pivotal study, a prospective, open-label, controlled, randomized clinical trial that demonstrated the safety and effectiveness of gammaCore as an adjunctive therapy for the preventive treatment of cluster headache. The second study reviewed by the FDA was a real world retrospective study examining the daily clinical use of gammaCore preventively and acutely for the treatment of cluster headache.

In the PREVA study, intention-to-treat (ITT) patients who received the standard of care and gammaCore (SoC plus nVNS, n=45; control, n=48) during the randomized phase had a greater reduction from the baseline (−5.9) in the number of cluster attacks per week than those receiving standard of care (−2.1), for a mean therapeutic gain of 3.9 fewer cluster attacks per week (P=0.02). In the site-adjusted model, the mean therapeutic gain was 4.2 fewer attacks per week (P=0.02).

Furthermore, 40 percent of patients who received gammaCore in addition to standard of care experienced a 50 percent or greater reduction in weekly cluster attacks, compared to 8.3 percent of patients who received standard of care alone (P<0.001).

In addition, there was a 57 percent decrease in the frequency of abortive medication use among patients who received gammaCore plus standard of care (P<0.001), while patients who received standard of care alone did not experience a substantial reduction in abortive medication use (P=0.59).

Here’s a video showing how to use the gammaCore Sapphire, the latest version of electroCore’s nVNS therapy:

Flashbacks: Vagus Nerve Stimulation for the Masses: Interview with electroCore CEO J.P. Errico…gammaCore Sapphire Helps Control Migraines and Cluster Headaches: Now Available in U.S…gammaCore Personal Non-Invasive VNS Cleared for Episodic Cluster Headaches…

Product page: gammaCore…

Via: electroCore…

Nanopore Sensor Exploits Artificial Intelligence for Specific Virus Detection

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Researchers at Osaka University in Japan have developed a nanopore sensor to detect single influenza viral particles in a biological sample. The researchers used artificial intelligence to work out the “hallmarks” of the virus, which allowed them to identify it using the sensor. The technique has potential as a point-of-care diagnostic tool for influenza patients, which could be very helpful in case of a dangerous outbreak.

Influenza infects millions of people every year. In vulnerable patients, such as the elderly, the infection can prove fatal, and there is an ever-present risk of a global flu pandemic, which could have catastrophic consequences. Given that the virus is highly contagious, in the case of a dangerous flu outbreak, rapid, sensitive and accurate diagnosis is extremely important, ideally at the point of care.

Current methods to identify the virus include genetic techniques, but conventionally these are not particularly rapid, and can require highly trained staff and specialized laboratory equipment, making them difficult to apply at the point of care.

To overcome this issue, this research group devised a new diagnostic approach that combines artificial intelligence with a nanopore sensor. The sensor involves creating a flow of liquid through a nanopore using an electric current that spans the pore.

The system allows only viral particles to pass through the nanopore, meaning that the sensor is highly specific, even when analyzing complex biological fluids containing numerous components. The device is also extremely sensitive, theoretically allowing the detection of single viral particles. The researchers used an artificial intelligence technique to identify the viral signature.

“We used machine-learning analysis of the electrical signatures of the virions,” said Makusu Tsutsui, a researcher involved in the study. “Using this artificial intelligence approach to signal analysis, our method can recognize a slight current waveform difference, which cannot be discerned by human eyes. This enables high-precision identification of viruses.”

The system may also be useful in detecting other types of virus, suggesting that it could be deployed in a variety of contexts for rapid point-of-care diagnosis.

“Our testing revealed that this new sensor may be suitable for use in a viral test kit that is both quick and simple,” said Akihide Arima, another researcher involved in the study. “Importantly, use of this sensor does not require specialized human expertise, so it can readily be applied as a point-of-care screening approach by a wide variety of healthcare personnel.”

Study in Scientific Reports: Selective detections of single-viruses using solid-state nanopores…

 Via: Osaka University…

Continuous Glucose Measuring Smartwatch, K’Watch Glucose, Expected Soon

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PKvitality, a company based outside of Paris, France, has announced that it’s getting ever closer to unveiling the world’s first glucose measuring smartwatch. The K’Watch Glucose, as it’s expected to be called, features the company’s patented SkinTaste technology that samples glucose from the skin and K’apsul biosensor that does the measuring. The biosensor has to be replaced every so often, and so will have to be purchased regularly as a consumable.

The watch is supposed to be able to continue measure glucose levels in real-time, providing results when needed and eventually triggering alarms to warn users of abnormal levels. This would be done on the watch and through a paired smartphone.

“PKvitality’s patient centric DNA is revealed in every K’Watch Glucose development’s detail. With PKvitality we conducted face to face usability tests with T1D patients, an approach that is still too rare at this stage of development of medical devices”, says Remy Leroy, head of diabetology in Hospital La Louvière Lille.

The company says it has seven patents pending related to its technology and in vivo testing has shown promising results. The K’Watch Glucose was an honoree at last year’s CES and also the winner of the “Best of Innovation” award.

Any excitement felt about this technology should come with a good deal of skepticism, as bold claims about accurate and painless glucometers have been made in the past.

Here’s a promo video for the yet-to-be-released device. Do note that the video shows it being activated to make individual readings, but the company has just confirmed that this won’t be necessary and the measurements will be continuous:

Via: PKvitality…

NYU and Facebook Release Database to Teach AI to Read MRI Scans

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Imaging scans, such as those taken using MRI machines and CT scanners, are hot targets for artificial intelligence research. Improving how well and how fast radiologists can spot lesions and other tissue characteristics can significantly improve the effectiveness of medicine overall. One problem regularly faced by researchers in this field is a shortage of data to work with.

To help with this, the NYU School of Medicine has partnered with Facebook to make public a giant database of knee MRI scans and related data. The collaborators of the project, called fastMRI, hope that other researchers can use the data stash to create software to spot different characteristics on MRI scans for different conditions and diseases. NYU and Facebook is working on their own AI software to analyze imaging scans, but they’re also building tools to help others developing similar applications.

The database includes over 1.5 million images from about 10,000 scans. 1,600 of the scans come with various anatomical measurement data. All the scans have patient information permanently removed and the database is fully HIPAA compliant. To soothe any recently rattled nerves, the announcement from NYU School of Medicine states that “No Facebook data of any kind are used in the project.”

Link: fastMRI…

Via: NYU School of Medicine…

Inkrypt and Translo Partner on Blockchain-Based, Secure, Shareable Healthcare Data (Interview)

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Last month, two startups out of Harvard Innovation Labs announced a partnership to enable patient-controlled sharing of biomedical data from a decentralized platform. The underlying system is provided by Inkrypt, a privacy-centric decentralized content hosting platform. Inkrypt uses a decentralized storage architecture, blockchain technology, and an anonymity overlay to ensure secure, tamper-evident, and censorship-resistant hosting and delivery of data. Building on Inkrypt is Translo, a decentralized, patient data-sharing platform that accelerates scientific achievement by catalyzing collaboration in biomedical research. Translo is working to provide a permissioned access system in an interoperable format for various types of healthcare data, including electronic patient health records and genomic data.

The partnership will combine Inkrypt’s secured cloud hosting service with Translo’s permission access platform. This provides robust security to protect Translo’s interoperable data from unauthorized access. Translo also plans to operate a data access request system and a search algorithm for its data on the Inkrypt network.

“Translo is tackling the fundamental flaw of data silos and lack of interoperable data formats in the healthcare and pharma industries. Enhanced collaboration and data sharing, in a unified format between these institutes, can revolutionize pharma and healthcare research and solve the dire issues we face in the fields of diagnostics, treatments and cure,” says Dr. Muhammad Ali Chaudhary, Co-Founder of Inkrypt. Commenting on the partnership, Kamran Khan, Co-Founder and CEO of Translo adds, “We firmly believe that privacy is a fundamental human right, therefore our partnership with Inkrypt makes perfect sense. By utilizing Inkrypt’s robust storage infrastructure, we can focus our efforts on other key aspects of our development.”

To learn more about Inkrypt, Translo, and the partnership, Medgadget had a chance to hear from Dr. Chaudhary as well as Farhan Javed, Co-Founder and Corporate Development Lead from Inkrypt and Kamran Khan from Translo.

 

Dr. Chaudhary, Co-Founder & System Architecture Lead, Inkrypt

Medgadget, Michael Batista: Thank you for taking the time to tell us about the recent partnership between Inkrypt and Translo. To begin, tell us a little about the motivation behind Inkrypt and what sets Inkrypt apart in the market, as well as from competitors?

Dr. Chaudhary, Co-Founder & System Architecture Lead, Inkrypt: The principle behind Inkrypt is that open access to authentic and resilient information is the bedrock of a free society. With all of Inkrypt’s founders deriving their origins from geographies with restrictions on free flow of information, they have experienced censorship first hand and realize the impact of censorship on society. In this context, they set out to create a platform that provides secure, private, and censorship-resistant cloud hosting services to the masses.

Inkrypt’s novel coupling of a decentralized encrypted storage architecture and an anonymity overlay sets it apart from other decentralized storage solutions as it not only provides data resilience and protection through distributing multiple encrypted copies of content across many storage nodes on the network but also ensures unhindered access to data for appropriate personnel by cloaking all network communications in a layer of anonymity. This makes tracking, compromising, hacking, or censoring data extremely difficult for any malicious actor.

 

Medgadget: Let’s get a little more technical. What are the components to Inkrypt’s cloud-based hosting platform? Can you explain how each component of the platform contributes to Inkrypt’s overall objectives?

Dr. Chaudhary: The Inkrypt platform is based on three main components: distributed storage architecture, anonymity overlay, and blockchain incentive structure,

(1) The distributed storage architecture divides content up into small fragments that are encrypted, replicated, and stored across the network on different storage nodes using a graph-based data management system. This technique of distributing redundant copies of file fragments across the network ensures persistence of content on the network as well as efficient query and reproduction of data upon request.

(2) The anonymity overlay shrouds all communications on the network so data in transit cannot be monitored. This anonymity protects data when it is moving from one device to the other and also ensures that the privacy of the publishers, storer, and accessor of information is maintained. This private communication system also adds an extra layer of security to the data on top of encryption.

(3) The blockchain forms the base layer of the Inkrypt protocol and creates an incentive model for data storage and delivery that ensures that the network is sustainable and efficient. Clients that want their content hosted on the network have to pay a fee for their hosting needs while storers and distributors of content need to be compensated for providing resources to the network. This exchange of value, between parties, is recorded on the blockchain, with the accompanying metadata associated with the content, in the form of a smart-contract that governs the hosting of content on the network.

 

Medgadget: Who will be using Inkrypt in the future? What are some specific use cases for Inkrypt’s platform?

Dr. Chaudhary: Inkrypt is slated to launch its testnet (an alternative blockchain used for testing) in Q1 2019. This launch will be coupled with the release of multiple decentralized applications (DApps), the most noteworthy of them being nLIGHTn. Multiple strategic partners are also building on top of Inkrypt.

nLIGHTn is a secure and censorship-resistant publishing platform for content creators and citizen journalists. With all the basic capabilities of publishing, peer-to-peer interaction, and the ability to form social groups, nLIGHTn can be used as a template to build social media, micro-blogging, and other social interaction DApps in the future.

In addition to these DApps, through strategic partnerships, Translo, a healthcare data-sharing company, and Poet, a content attribution/licensing service, are actively building on top of Inkrypt.

In the future, Inkrypt will fulfill the needs of all industry verticals that require a secure, efficient, and private cloud hosting solution. This list includes, but is not limited to, banks and financial institutions, hospitals, public records, social media, as well as media and entertainment.

 

Kamran Khan, CEO, Translo

Medgadget: Shifting gears, can you tell us about Translo’s platform and capabilities?

Kamran Khan, CEO, Translo: Translo is a privacy-preserving biomedical data-sharing platform built to accelerate biomedical discoveries. Translo creates a mechanism to convert various electronic health record formats to FIHR HL7 interoperable format. Through two different portals, we give clinical trial teams access to anonymized EHR data that they can then use to shorten the cycle for patient recruitment – something that is made incredibly complicated due to inclusion/exclusion criterion. Our user-facing platform also allows this EHR data to be paired with Real World Evidence, which is the true cost-saver for most drug development platforms. By leveraging this real-time clinical data, Translo can identify patients and sites that match the eligibility criteria for pharmaceutical companies and Contract Research Organizations (CROs). In addition, Translo is developing an analytics platform that helps CROs better access this data and gain insights. This enables efficiencies and drastically reduces the time to market.

To summarize, Translo’s value proposition lies in the following features:

 

  • Interoperable healthcare data
  • Distributed and secure data hosting to ensure PHI protection and HIPPA compliance
  • Patients ownership and complete autonomy over healthcare data
  • Real World Evidence (RWE) to support clinical trials’ protocol design and patient selection
  • A global marketplace for data exchange

 

Medgadget: How does Translo aggregate health care data on its platform from various sources? How is health care data stored and accessed by users?

Khan: Translo primarily aggregates health care data through partnerships with small and large patient care centers where patients want to connect to clinical trials. Doctors release data for patients that agree to be a part of the platform and Translo takes that data and anonymized it, only giving companies access to non-PHI (patient health information). Information Translo does not share would include identifying information such as name, address, phone number.

Data from different formats is taken and then converted to a standardized FIHR HL7 protocol while being stripped of all PHI, allowing for greater transparency and ease of use for organizations looking to run analytics to improve patient care. PHI information is hashed and is stored at the partner’s site. Data is then encrypted and stored on Inkrypt’s decentralized anonymous cloud. The data storage is off-chain and encrypted in secure data vaults on the Inkrypt network. Organizations looking to recruit patients have access to the data that is easily searchable.

Translo utilizes a blockchain layer to manage identity and data access permissions. Using smart contracts, Translo can control data access on a granular level to enforce HIPPA compliance. This provides an audit trail and ensures data is accessed in a permissioned manner.

 

Medgadget: Who will use Translo’s platform and what will they use Translo for?

Khan: Translo’s testnet is scheduled to launch in Q2 of 2019. Upon launch, Translo’s ecosystem will provide services to patients, biopharmaceutical companies, CROs, and healthcare organizations.

Translo provides patients with their longitudinal healthcare records through the patient portal. This empowers patients, allows them to share this data directly with their caregivers, and enables them to sell this data directly to biopharmaceutical companies as part of their Real-World Evidence endeavors. In addition, this portal establishes a direct communication channel between biopharmaceutical companies and patients for clinical trial purposes.

Currently, site and patient recruitment is a relationship-driven pursuit and is prone to overestimation of patient availability. Translo utilizes real-time clinical data to match sites and recruit patients for a given clinical trial due to the complexity of inclusion/exclusion criterion. It currently takes someone running a clinical trial months to find the right candidates to participate. Our platform will allow them to shorten this timeline by 90% because 60% of the information needed to determine whether a patient fits this criterion is part of our database. Random forest modeling allows Translo to fill in the data gap for information not currently present. This significantly decreases patient recruitment timelines and enables biopharmaceutical trials to fulfill their recruitment goals.

CROs lack real-time clinical data and therefore are challenged to bid for projects effectively. Translo provides clinical data and the analytical tools to adequately assess availability of a cohort at a given site. This allows CROs to bid for appropriate projects and avoids unnecessary protocol amendments.

Finally, Translo enables healthcare organizations to attract more clinical trials so they can generate additional revenue and aide in developing new therapies.

 

Farhan Javed, Co-Founder & Corporate Development Lead, Inkrypt

Medgadget: Where did Inkrypt’s interest in partnering with Translo come from?

Farhan Javed, Co-Founder & Corporate Development Lead, Inkrypt: Inkrypt is an infrastructure project that is creating an ecosystem of security, privacy, and censorship-resistance. As a result, high-impact verticals that deal with very sensitive data, such as healthcare and the usage of patient information, became spaces of interest to us. Healthcare was also a vertical that Inkrypt’s team was comfortable with as Dr. Chaudhary, one of our co-founders and System Architecture Lead, is a physician by training and uses big data methodologies to answer health-policy related questions as a researcher at the Harvard Medical School and Harvard T.H Chan School of Public Health. Further, like Inkrypt, Translo is also a thriving participant in the innovation ecosystem at Harvard and a leading venture based at the Harvard Innovation Labs. This has allowed both teams to grow close, attain a nuanced understanding of each other’s value proposition, and identify synergies.

 

Medgadget: What benefits do both Inkrypt and Translo gain from the partnership?

Javed: The value proposition of Inkrypt hinges on providing secure and censorship-resistant data hosting for sensitive data. Healthcare and financial data are, perhaps, the most sensitive types of data hosted on the internet. A partnership with Translo gives Inkrypt the opportunity to showcase its robust security and data access system for other use cases. Additionally, the network traffic Translo brings to Inkrypt will be invaluable to bootstrap the network and make it sustainable.

Khan: Translo handles patient data so extreme diligence is required to shield sensitive protected health information from cyber breaches. Therefore, a partnership with Inkrypt not only ensures data security, but Inkrypt’s anonymized communication system also provides protection for data in transit in the Translo ecosystem. This is a necessary solution for the healthcare industry and Translo is excited to join hands with Inkrypt in tackling this issue together.

 

Medgadget: Which blockchains do Encrypt and Translo use today? Can you comment on the interoperability between two different blockchain-based technology platforms?

Dr. Chaudhary: Inkrypt, by virtue of its modular architecture, is blockchain agnostic. The blockchain only provides the base incentive layer for the protocol and any smart-contract enabled blockchain can be used for this function. Currently, Inkrypt is building its blockchain layer on the RChain ecosystem due to its virtually infinite scalability and concurrent processing capabilities.

As Translo is a data access control and permission system for healthcare data, hosting contracts will be processed on Inkrypt’s native ecosystem while the data permission system is going to run on Tranlso’s protocol, allowing for HIPPA compliance and seamless integration with Inkrypt’s hosting services.

 

Medgadget: How does Inkrypt differ from other blockchain-based storage platforms like Filecoin?

Dr. Chaudhary: Inkrypt’s core differentiation from Filecoin is native anonymity. We are the only decentralized storage protocol that totally operates outside of the clearnet and makes use of anonymized nodal communications.

Native anonymity is crucial for user privacy and unhindered access to data. IPFS (InterPlanetary File System), Filecoin’s underlying protocol, uses an IP address (i.e. geo-location)-based peer identity system. All network communications on IPFS are visible on the clearnet. Even if you were to use a Tor connection with IPFS, the anonymity of the accessor might be preserved but the node serving as gateway is still visible and can be blocked to impede access to information. This means that malicious actors can still easily geo-locate nodes and impede the flow of information using IP blocks. This happened in Spain during the Catalonia Referendum when people were trying, unsuccessfully, to use IPFS to circumvent Spanish censorship. This is likely what would also happen if IPFS tried to operate in other censorship-prone regions.

On the Inkrypt network, all communications between the nodes are on i2p, the Invisible Internet Project, which ensures the whole network is cloaked from discover. Peer identity is established through cryptographic identity rather than IP address.

 

Medgadget: To close, for Translo, a number of companies, including EMR themselves, are beginning to create pathways for health data exchange. Why is Translo a differentiated approach to interoperability that will gain traction in this busy market?

Khan: The difference lies in ownership. Right now, hospitals and data-holders are the owners of the information, and the patient has no control over their own healthcare data therefore derive no benefit from its utilization. However, with Translo’s patient-centered ecosystem, the patient owns their healthcare data. The individual is in complete control of who can access their data, know how it is being used, and gain benefits in two key ways: (2) monetary benefits from use and (2) depending on what type of data they give, they’ll be the first to know about potential clinical trials and have the fastest pathway to enrollment.

Translo creates interoperability between electronic health record systems and offers complete longitudinal health records for patients. This enables biopharmaceutical companies to access complete histories of patients, which has not been the case historically. Moreover, Translo create a direct mechanism for biopharmaceutical companies to search for data and run analytics on Translo’s platform instead of solely relying on third party biomedical data brokers. These efficiencies are a value add and sets Translo apart from the competition. Lastly, Translo utilizes a blockchain layer and distributed storage to ensure privacy and security beyond HIPPA compliance. We strongly believe that ensuring trust and security will promote data-sharing between patients and institutions.

Links: Inkrypt and Translo…

Announcement: Inkrypt forges partnership with Translo to provide secure decentralized hosting to healthcare…

GE Healthcare’s New Revolution Apex CT with Deep Learning Image Reconstruction

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GE Healthcare unveiled a new CT scanner in its lineup of Revolution family of devices. The Revolution Apex device features the brand new Quantix 160 X-Ray tube and Deep Learning Imaging Reconstruction, a system built on GE’s Edison platform to produce “TrueFidelity” images in challenging cases.

GE believes it offers the “industry’s leading spatial resolution, temporal resolution, coverage and spectral capability” and that the new X-ray tube and underlying software will provide even better results.

The company says that the images have an improved, natural look that’s not so grainy, a high spatial resolution, and low contrast detectability. This allows entire organs to be imaged in high quality while seeing suspicious low contrast objects.

GE also provides five new CT Smart Subscription Packages for its scanners to improve their capabilities for specific applications:

• Reconstruction Package: Improves low-contrast detectability while reducing patient radiation dose and artifacts
• Image Quality Package: Offers exceptional image quality to reveal anatomic details obscured by metal artifacts and helps clinicians utilize CT scans and diagnose disease with greater confidence
• Cardiac Package: Increases reliability and repeatability of complex cardiac imaging procedures and readability of resulting images
• Neuro Package: Provides faster and more accurate assessments of stroke and head trauma
• Oncology Package: Delivers edge-to-edge image acquisition with virtually no blind spots

Via: GE Healthcare…

Medgadget Sci-Fi Contest 2018: Meet The Authors and Read Their Stories

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From Jules Verne to Isaac Asimov, science fiction writers have inspired scientists, explorers, and thrill seekers to influence the future of humanity. While Sci-Fi may seem like it’s about the distant future, more often than not it’s commentary on rudimentary technologies that already exist and that are about to mature and reveal their true potential.

The authors of this year’s Medgadget Sci-Fi Writing Contest are certainly in tune with the latest trends in biomedicine, the introduction of artificial intelligence (AI) into clinical practice, and genetic manipulation taking place in thousands of labs around the world.

We would like to thank Eko Devices, the wonderful sponsors of our contest, that make the coolest and most advanced digital stethoscopes out there. The first place winner of our contest will receive an Eko CORE stethoscope that is both acoustic and electronic, has all the features of both, can amplify sound, record audio waveforms, connect to your phone, and let you share auscultations with your colleagues. Thank you, Eko!

The second and third place winners will each receive a $50 Amazon gift card, courtesy of Medgadget.

We asked the three winners to tell us a little about themselves. Here’s who they are, followed by their fantastic, and unexpected, stories.

1st Place:

To our delight, Yih Yang (Ian to his friends), was the 2nd place winner in last year’s Medgadget Sci-Fi Writing Contest. He is an aspiring PhD student with dreams of eventually attaining his degree in Biomedical Engineering. In the meantime, while waiting for his cells to grow into organoids, and while he’s sitting in the dark waiting for his microscope to finish imaging them, he gets strange ideas about the future of science and medicine. Sometimes, some of these ideas manage to crystallize into something remotely plausible! He likes to write these ideas into science fiction stories, and hopes to bring the technologies described within them to reality with his actual scientific career. We very much approve of his approach to time management in the lab and that he gets to share with us the imagination that hours of waiting for the organoids to mature affords him.

2nd Place:

Our second place winner is Dr. Mohamed El Wazir, an Egyptian cardiologist who’s currently doing research at the Mayo Clinic. He is also a computer developer with a special interest in AI, and an avid reader of futuristic Sci-Fi series, Altered Carbon and the Revelation Space collection being among his top favorites. He’s relatively new to writing, however, with this story being his first published work. Dr. Wazir’s short story is eerie, deceptive, and should give some warning to bioscientists.

3rd Place:

Niamh Davies-Kelly is a third year medical student at the University of Liverpool School of Medicine. He wrote this plot because he thinks it’s interesting to weigh up the positives and negatives of technological advancement. As he relays, “we know to the best of our ability that how we do our jobs/future careers works and does improve lives, however it’s important to always remember it could always be done better.”

Outside of his studies, which take quite a lot of Niamh’s time, he’s very much into horse riding and is the captain of the intermediate riding club for the University of Liverpool. When he has a moment, he likes to do something a bit more creative than making notes, whether this be writing or drawing!

 

1st Place, Yih Yang

Synchrony

“So this is what my dad’s brain looks like on the inside?” Kathleen said, waving vaguely to the holographic image around them. She recognized the characteristic wrinkles, and watched as they turned into maze-like traces as they wound deeper into the brain. The hologram appeared solid, but if she squinted, Kathleen could make out billions of cells, all glowing as they rotated around them.

“Well, it’s every neuron that carry the minimum detectable amount of the transceiver nanoparticles within.” John gestured to the billions of cells that hung around them, each only a pinprick of light within the vast tapestry of the brain. “Judging by the number of cells that are showing up here, and compared to the number of neurons in the average human male brain, I can say that we’ve managed to get our nanoparticles inside roughly 94% of your dad’s neurons.”

“But how much progress have we made?” she asked quietly, as lights flashed chaotically throughout the brain.

“Using the data from previous sessions, SYNAPSE has achieved about 28% synchrony. Don’t be discouraged though, since memory restoration is going to be non-linear. We’ll probably get a spike in synchrony from today!” John reassured. He looked down at his desk quickly, to prevent her from seeing the worry in his eyes. “The session is about to begin, please have a seat.”

Kathleen shuffled to the chair that she had used in all of the previous sessions, and settled onto its uncomfortable metal seat. She had gotten used to its cold bite, and stared through the one-way window in front of her. It looked into an adjoining room, where her father and a doctor were seated in comfortable couches, facing a large screen that filled the entire opposite wall. A helmet adorned with blinking lights covered her father’s head, with dozens of wires and cables connecting it to the ceiling. He fidgeted irritably in his seat and half-heartedly tried to remove the heavy helmet before being stopped by the doctor.

“Mr. Stevens, the helmet has to stay on until the session is over, OK?”

“It’s heavy and it’s pressing into my head! I want it off!” he demanded.

“Mr. Stevens, if you don’t wear that helmet, then we can’t help you.”

“I don’t need your help! You doctors are all a bunch of quacks! I don’t need all these fancy contraptions to live my life! Why don’t you just let me go!?”

“Mr. Stevens, you only have to be here for a couple of hours, then you are free to go.” The doctor replied patiently.

“Fine! But I want steak! I want it now!”

Dr. McAllister suppressed her frustration by tucking a lock of her red hair behind her ear. “That could be arranged, if you answer my questions as best as you can remember, all without taking off your helmet. Do we have a deal?”

“Fine, fine, let’s get it over with.”

Kathleen leaned back from the one-way window and sighed quietly. “I still can’t get used to how different he is. Before he got infected, he wasn’t impatient, brash, or irrationally demanding.” She glanced back at John, and caught a glimpse of worry in his eyes before he looked away. “Do you still think we can still complete the treatment before we run out of time?”

“I admit, normally we’d be done with memory restoration by now. Although, we usually remove PTSD-causing memories from patients.” John said sheepishly.

“What’s the problem then?”

“Well, for SYNAPSE to correctly map out your father’s entire memory network, I have to give it guidance and tell it which neurons are linked together into a memory engram. SYNAPSE would take this information, and see if these neurons are responsible for storing other memories. If there are overlapping cells, then we could stimulate those and discover secondary memory engrams, and so on, and thus construct a neural network of your father’s mind.”

“Right, and then you use the transceivers in my dad’s brain to synchronize the cells that hold the same memory and strengthen my dad’s ability to recall them.”

“That’s correct.” John pointed at the holographic brain, where the progress bar had stopped. “There’s this one pattern that looks like a memory engram, but doesn’t seem to attach to any specific event. It’s screwing up SYNAPSE and preventing the AI from reconstructing your father’s neural network any further beyond 28% synchrony. SYNAPSE calls it Pattern Theta, and it intersects with almost all of the memory engrams that I’ve identified. But I’ll figure this out.” John waved at the window, “Doctor McAllister is starting!”

In the other room, Dr. McAllister directed Mr. Stevens’ attention to the large screen in front of him, “Mr. Stevens, I’m going to play a video and then ask you some questions after it ends, ok?”

Mr. Stevens grunted and waved his hand impatiently.

Dr. McAllister pressed a switch on her chair and spoke clearly into the room, “Session 15, Goodman High School Event.”

The screen flickered as an old wood-and-brick schoolhouse appeared. Hundreds of people were staring at the schoolhouse from behind police lines, watching flames lick their way up through the building from the ground. Several news vans could be seen amongst the crowds, with many correspondents jabbering into microphones and interviewing the people around them.

A news reporter ducked reflexively as a large gout of flame blew out several windows on the ground floor. “As you can see, the fire is still raging behind me at Goodman High School.” She gestured to the burning building behind her frantically, “Most of the students have been evacuated, along with all of the teachers and staff. However, I’m getting reports that a few kids are still inside the building.”

Behind her, several firefighters battled the blaze with constant torrents of high-velocity water. A figure emerged through a blown-out window, carrying a kid under each arm. He handed them off quickly to another firefighter before turning back. “I saw another girl in there. I’m going back in!” The firefighter roared before diving back into the flames.

Kathleen frowned as she noticed a few tufts of smoke whirl into the room with her father and Dr. McAllister. She saw the doctor loosen her collar as sweat beaded on her forehead. “Wait, what’s going on?” She asked John, as the video on the screen suddenly switched into a first-person perspective, presumably of the firefighter.

“We’re making the experience as vivid as possible, so that we can trigger the real memory in your father’s brain.” John replied, gesturing to the holographic brain. Lights bloomed and flashed all over the amygdala, as well as a few weak flashes within the cerebellum and ventral temporal lobe. “The more real we can make it seem, the greater chance that we can identify all the neurons that are responsible for this experience, and then synchronize them to make the memory stronger, and more permanent.”

The lights in the viewing room flashed orange and yellow, as if to simulate the flickering light of the flames. Heavy breathing could be heard over the speakers, as Kathleen watched the firefighter struggle through the burning building. A fiery timber slammed onto the floor in front of him, making him flinch and blocking off his access as it leaned against the wall.

Kathleen could see light flash amongst the left side of the brain as the firefighter reached out with his right hand to push the timber away. It rolled and fell off the wall, sending a cloud of sparks bursting upwards from where it impacted the floor. “I’m almost there!” he called, “Stay where you are.”

He strode through smouldering furniture and found a red-haired girl hiding underneath a still-unburnt desk. Tossing her over his shoulder, he carefully picked his way around the flames and arrived at another broken window. He cleared off the shards of glass before stepping through and out onto the school lawn. The crowd cheered as he marched towards them, smiling broadly with a toothy grin. He set the red-haired girl down and she immediately ran into her parents’ arms.

“Why did Dr. McAllister want my dad to relive this event?” Kathleen asked as she watched a younger version of her dad join the other firefighters. They continued to douse the flames with water, and slowly the blaze died out.

“Well, we needed another defining event in his life, to trigger as many neurons as possible that are associated with this memory.” John explained, “Because of your father’s brain injury, those neurons aren’t going to be synchronized when he tries to recall the memory, so we need an experience as rich as possible to trigger all of the associated neurons.”

“I know that, but it just seems different than all the other memories that we’ve used.” Kathleen said as her father’s younger self was approached by a news reporter. “He’s seen videos of his graduation, wedding, various awards ceremonies, trips from our family vacations, and even my birth! It’s strange that this specific fire would be chosen out of his long firefighting career to restore his memory network.”

“Trust Dr. McAllister’s judgement. Let me enter this data into SYNAPSE. Maybe we’ll see a drastic increase in synchrony!” John tapped some commands into his keyboard, and immediately the holographic brain began to rapidly blink and flash, with billions of lights going on and off chaotically. A progress bar materialized over the brain, slowly filling up as SYNAPSE integrated all of the collected data and started to reconstruct Mr. Stevens’ memory network.

A small voice, which Kathleen recognized as her own, issued from the speakers. Another small girl ran up to her father in the video, stretching out her arms for a hug.

“There’s my little rabbit!” Younger Mr. Stevens picked up a much younger Kathleen, and placed her on his shoulder.

“Dad, you were so cool!” Young Kathleen said as she pried off her dad’s helmet and played with his hair.

A news reporter thrust a microphone into his face. “Mr. Stevens, that was such a heroic rescue! What was going through your mind as you were walking through the fire?”

“I just knew that there was another girl in there and that it could have been my own daughter.” Mr. Stevens replied. He spotted the red-haired girl in the crowd, who waved sheepishly at him.

The video faded out and the lights came on slowly. Dr. McAllister nodded at John with a look of significance in her eyes, before beginning the post-video interview with Mr. Stevens.

Kathleen sat back and closed her eyes. She tried to fight the anxious knot in her chest from expanding, and suppressed the negative thoughts that threatened to surface. As she understood it, this would probably be the last session that they had before the transceiver nanoparticles in her father’s neurons would degrade and pass out of his body. She didn’t understand why they couldn’t just re-inject him with more nanoparticles once that happens. John said something about her father’s body adapting to the viral nature of the nanoparticles and developing an immunity against the treatment.

John muttered under his breath. “There it is again.”

“Pattern Theta?”

“Yeah, but it looks… different.”

Kathleen turned away, fighting the tears that tried to squeeze out of her eyes, “So we won’t be able to restore my dad’s memories in time?”

“I…,” John hesitated. “We have 38% synchrony now, and if I cross-reference your father’s memory engrams with those of the average human male, I think I could reach 80-90% synchrony.”

“I don’t want the average human male.” She replied quietly, “I want my dad back. I want the person who raised me, who taught me to be patient and kind to everyone around us.” Kathleen placed a longing hand on the window, “I want the man that he was, before he got infected with that stupid disease that ate away his memories and his soul.”

John studiously stared at the holographic brain, knowing anything he said was going to make Kathleen feel worse.

In the other room, Dr. McAllister asked, “Mr. Stevens, do you remember that schoolhouse?”

Mr. Stevens shifted in his seat, “A little. I remember the heat. Lots of scared kids.”

“Do you remember how it felt to carry one kid in each arm and save them both at the same time?”

“I felt…good.” Mr. Stevens replied uncertainly. He frowned in concentration, “I was…cool.”

“You were, Mr. Stevens.” Dr. McAllister leaned in closer towards him, “What did you see when you looked into the crowds? Were there people that stuck out from the crowd?”

“Just a lot of parents worried for their kids’ safety.” Mr. Stevens replied dismissively.

“What happened to the last girl that you carried out of the fire?” Dr. McAllister persisted.

“She ran to her parents, of course.” Mr. Stevens paused and cocked his head, as if the question was prying a thought loose, “She…waved back.”

“OH!” John involuntarily blurted, “Pattern Theta…”

“What?” Kathleen asked as she watched her father reach forward and bring a lock of Dr. McAllister’s red hair closer for inspection.

“Your hair is more red than it was that day.” He said whimsically.

“It grew redder as I grew older.” Dr. McAllister smiled.

“Why didn’t she say anything?” John muttered as he furiously typed into his keyboard. “Maybe she didn’t want me to exclude those engrams as external noise?”

“Dr. McAllister is that red-haired girl?”

“More than that: Dr. McAllister is Pattern Theta.” John answered as he set SYNAPSE loose on the new data, “And because she’s been interviewing your father in all of the sessions, Pattern Theta keeps activating. And with both past and present versions of Pattern Theta, I can also tell SYNAPSE how your father’s memory encoding has changed throughout the years!”

He pointed at the progress bar above the brain, which was rapidly filling up. It finally stopped, to Kathleen’s delight, at 92% synchrony. “Not bad, eh?” John said, smiling at her, “Should I tell the nano-transceivers to begin the synchronization process using SYNAPSE’s instructions?”

Kathleen stared rapturously at the holographic brain, dazzled by the sheer amount of flashes that the neurons were emitting. Instead of the chaotic blizzard of light and colour that she was used to seeing, all of the flashes of the same colour were blinking at the same time, at the same rate. It was a visual symphony, carefully choreographed as the memory engrams danced around each other in time, never overlapping or interfering with one another. She nodded wordlessly.

Dr. McAllister smiled as the helmet lit up. “Good news, Mr. Stevens, we have enough information to restore your memories now. Just lean back and take a nap. You’ll wake up feeling like yourself again.”

Mr. Stevens looked at her curiously, then leaned back and closed his eyes. “Where’s Kathleen?”

Dr. McAllister pushed a button on her chair, and waved at the window. Kathleen cleared her throat and spoke quietly over the speakers, “I’m here dad.”

“There she is.” Mr. Stevens smiled. “There’s my little rabbit.”

2nd Place, Dr. Mohamed El Wazir

The Father

“Alert. Ventricular fibrillation,” announced Mr. Wilson’s telemeter in a cool female voice that seemed completely incongruous with the ear-piercing siren which blared half a second later. “Delivering asynchronous DC shock in two… one-”

NOW, Amy!” yelled Jerry.

The word had barely left his lips when Mr. Wilson gave a violent jolt, and the siren stopped.

“Sinus rhythm restored,” declared the telemeter indifferently. “Significant early after-depolarizations detected in right ventricular apex. Probability of recurrent ventricular fibrillation over 60%. Medullary modulating pulses at 55 kHz are recommended. Commence?”

“Yes please, Amy,” Jerry said. He hesitated for a moment, then grumbled, “Thank you.”

“Acknowledged, Dr. Jones,” replied the female voice, with what Jerry felt to be amusement. He knew he was being silly, that his resentment towards this new system was making him imagine things, yet he still couldn’t shake it off. As much as the new system made his job easier, Jerry hated its guts.

He flopped onto an empty gurney and eyed the little black box attached to the siderail of Mr. Wilson’s bed with hostility. Jerry had been an emergency physician for three years, and the last two months had been his worst. His hospital was one of the last in the state to apply the new system. Artificial Intelligence Medical Interface, AIMI for short. Everybody simply called it Amy, and as far as Jerry was concerned, giving it a human name didn’t make it any more likeable.

Before Amy, telemeters were just that: telemeters. Instruments. Tools, that doctors used to query a patient’s chip for a bioreadout and, when applicable, instruct the chip to deliver treatment. The chips themselves were not part of Amy. In fact, the government had begun mandating prenatal biochip implantation sometime around 2090. Today, over a century later, people without chips no longer existed. The procedure was relatively simple: the biochip itself was a tiny piece of circuitry embedded in the iliac crest in utero, along with an injection of self-regenerating nanobots into the blood stream. Under the biochip’s control, these nanobots had the ability to attach to any specific type of cell to collect information and relay it back to the chip, or to effect change by modulating various cellular processes. Naturally, the advent of biochip-mediated nanomedicine had rendered whole textbooks obsolete in record time.

And now Amy was here to make doctors obsolete. Sure, the system was supposedly run by doctors, but all Jerry really did for the past two months was okay the decisions Amy made. She never made mistakes, so there was never a need to correct her, but it felt emasculating, and it was all-too-obvious this was just a first step to doctors being ushered out of the picture completely.

“Bad shift, eh?”

Jerry looked up. It was Adam, the morning-shift physician on duty, striding up to him while dusting snow off his black trench coat.

“No, I’m just sick of sucking up to you-know-who,” complained Jerry, trying to mumble out of earshot of the telemeter. He probably didn’t need to bother anyway; Amy was wired into enough hospital equipment to make secrecy a futile endeavor.

“Yeah, aren’t we all,” snorted Adam, shrugging off his coat to reveal freshly ironed royal-blue scrubs. “Sheila from peds got suspended yesterday for yelling at her. ‘Inappropriate behavior’, they called it.”

Jerry shook his head disapprovingly before getting tiredly to his feet. “Log me out please, Amy,” he said to the telemeter. “Dr. Philip is here for the morning shift.”

“Acknowledged, Dr. Jones,” repeated Amy. “Have a nice day.” A short pause, then: “Good morning, Dr. Philip.”

Jerry left Adam exchanging the obligatory niceties with Amy and made for the coat room. His path took him through the medical ward, past a row of patient beds where first-year residents stood listening confusedly to their patients’ telemeters before someone more senior came along. A few of them – the less experienced – were trying to argue with their telemeters. One had actually opted to ignoring the telemeter altogether and talking to the patient, who seemed amused by the unusual attention. Most of the residents, however, didn’t talk back at all.

Jerry hated the medical ward. It was a dull place, basically a glorified waiting room where patients rested while doctors gave their chips instructions on how to fix whatever was wrong with them before sending them home. Before Amy, that interaction took place through a programmable user interface built into the telemeters. Now, even the modest challenge of accomplishing that task had been denied them, since they could just tell Amy what to do – or rather; she told them. Even their manual skills were rarely if ever needed. The nanos could do almost anything, up to stimulating stem cells to rebuild entire organs in-situ. Not that anyone reached that stage anymore. Surgical intervention was reserved for critical, massive-trauma patients whose injuries were beyond even the nano-accelerated regenerative capacity of stem cells.

A harassed-looking first year resident in blood-spattered girly-pink scrubs jumped abruptly in front of him, interrupting both his brooding and his path.

“Dr. Jones,” she panted. “We need you in Trauma-1.”

“Sorry, Linda, I’m off,” replied Jerry, walking around her. “Adam is back in Resus, he can help you.”

“Can’t you just take a look?”

Jerry sighed, slowing down a little. “What does Amy say?”

“Nothing!” blurted Linda. “That’s just it! I tried three telemeters. Only her name shows up: Julia Bell, but no other data. I think her chip is malfunctioning.”

Jerry stopped. “Is she a high-voltage electrocution? Or a bullet to the iliac crest?”

“No. Just a car accident.”

Jerry frowned. Outside of the two scenarios he had just mentioned, chip failure was virtually unheard of. Chips were made of high-durability semiconductor polymer and were built to last. He turned around to face Linda.

“Okay, I’ll take a look.”

Linda’s features relaxed visibly. “Thanks!” she said, letting him lead the way while she filled him in. “She was just brought in by EMS. Seems in her teens, no ID apart from the name on the chip. Hit by a robotruck. Coma level D2. Racoon eyes suggest likely fracture skull base, also right humerus and a couple of ribs. Her lumbar spine doesn’t feel right to me either. Vitals are stable, though.”

“That’s a pretty impressive assessment without a telemeter,” remarked Jerry.

“Thanks,” replied Linda, her face blushing to match her scrubs.

As they walked into Trauma-1, the small group of interns gathered around the comatose mystery girl’s bed dispersed to make way for Jerry. He saw that Linda had connected her to an old-school wired monitor. After a quick exam, however, he turned back to Linda in disappointment.

“Well, you were right about the humerus,” he said, “but I don’t see any racoon eyes, and the rib fractures are old – healed, in fact. Spine seems fine, too.”

“What? How?” asked Linda, stooping over the girl. “But… but, I swear there were racoon eyes! And her ribs were bruised and swollen!”

“Swollen, yes,” explained Jerry. “It’s called a healing callus. No bruises, though. That’s all right. It happens.”

Linda glanced at the onlooking interns and blushed again, a deeper shade this time.

“Okay, better get to work,” Jerry announced, addressing the interns to change the subject. “Can somebody get us an automold kit so we can immobilize this arm before sending her to M-scan? This is a good opportunity for you guys to learn some traditional medicine.”

***

Jerry was almost at the exit when Linda stopped him again.

“Linda, Adam is-” he began.

“Her M-scan is normal,” interrupted Linda.

“What? How?”

Linda shrugged. “See for yourself,” she said, taking off her interface glasses and handing them to him. Jerry put them on and spoke some instructions, and a magnified subanatomical model of Julia Bell’s body floated up in front of him, rotating slowly. Readouts and highlights corroborated what Linda had just said, but Jerry had to see for himself. He reached out and grabbed the model by the right arm, the glasses’ cameras seamlessly incorporating his hand gestures into the simulation. He fanned his fingers to zoom in, then started peeling off layers: skin, muscle, and fibrous tissue, before picking out the bone and turning it over in his hands. The humerus that was ten minutes ago broken clean in two, was now undeniably intact. Jerry switched through several tissue-filter view modes, but none of them showed anything wrong.

“Amy.”

A pretty but serious-looking thirtyish brunette in a duke-blue suit materialized in his glasses’ field of vision.

“Good morning, Dr. Jones,” she said. “You are not on duty. Should I log y-”

“No,” he interrupted. “Just tell me what you think about the scan I’m accessing.”

“It’s a normal scan,” replied Amy instantaneously. “I also note the absence of nanobots.”

“What?” Jerry said, looking back at model. “Nanobot filter,” he spoke, and the model vanished. What he was supposed to see in its place was a visual representation of nanobot density. What he was seeing, was nothing at all.

Jerry frowned at the empty air in front of him for a few moments, then turned to Linda. “Is she still in the scanner?” he asked.

“No, I brought her to the ward. Her coma scale’s improving. It’s now-”

“Take her back,” interrupted Jerry. “Let’s do a real-time scan. Even nanos can’t heal that fast; I wanna see what’s going on.”

They hurried back to the ward, where Linda stopped at an empty bed. “She’s gone,” she muttered.

“Of course,” Jerry said, nodding slowly to himself. “With a normal M-scan she should’ve been fully conscious. What you thought was an improved coma scale was actually her faking it so she could run away once you left.”

Linda started blushing again.

“Oh, don’t,” Jerry said. “You did great. Really. And sorry for correcting you in front of the interns, I shouldn’t have. Turns out you were right anyway.” He shook his head silently. “I just wish she’d stayed around until we figured out what was happening.”

***

Jerry spent the best part of the next month obsessing over Julia Bell. He’d tried looking her up of course, but a quick search had confirmed his suspicions: there was no Julia Bell matching her description. A hacked chip with a fake name. He reviewed her scan a dozen times, looking vainly for something he might have missed. How was she possible? Was she a part of some secret experiment? Every day he kept expecting a news announcement that someone had made a breakthrough in regenerative medicine, but that news never came. Eventually, Jerry began to let go, and a month later he had nearly forgotten about her.

That is, until he bumped into her outside his local WalkMart.

It was on a chilly February evening, three months after the day he had seen her at the hospital. He had just got off his shift, and decided to pick up some groceries on his way home instead of ordering online. As he strolled absentmindedly through the door, a shopping-bag-laden girl came rushing out and collided violently with him, sending groceries rolling all over the sidewalk.

“I’m so sorry,” the girl apologized, stooping to gather her fallen groceries.

“It’s okay,” reassured Jerry, crouching beside her to help. “I wasn’t paying-” he began, then froze.

The girl looked up to see why he failed to finish his sentence, and found him staring her dead in the face. It was a face Jerry had spent hours staring at through his interface glasses.

It was the face of Julia Bell.

Jerry recovered quickly, looked away and busied himself with the spilled bags. Once he finished helping her he hurried into the store, slid into an aisle and turned around to peek at her over the shelves. The girl looked back for a puzzled moment, then picked up her bags and started down the street. Jerry waited half a minute before following her, making sure to keep his distance.

He stalked her for nearly half a mile, until she arrived at a rather unremarkable two-story house and disappeared inside. Jerry crept up to a window and peered through, with no idea what he was looking for.

“HEY!”

Jerry whirled around. A bearded man in a robe was standing behind him with garden fork in his hands. In the dark, Jerry must have walked right past him without noticing.

“I, uh,” stammered Jerry, “I, I’m not a burglar.”

“Really?” the man said sarcastically, leveling the fork as he came forward. “Because you’re acting a lot like one.”

“No sir, please, I’m a doctor!” Jerry blurted.

The man stopped. “A doctor?” he echoed. Jerry thought he actually sounded scared. “What do you want?”

Jerry hesitated, but then decided to tell him everything. The man listened intently, his face darkening as Jerry went on.

“Did you tell anyone you saw her today?” he asked quietly when Jerry was done.

“No,” assured Jerry.

The man considered for a moment. “Let’s go inside,” he finally said.

Jerry followed him into the kitchen, where Julia was unpacking the groceries. She stopped when she saw Jerry, and frowned inquisitively at the man who seemed to be her father.

“Have a seat, doctor uh…” he prompted, gesturing toward an empty chair.

“Jerry.”

“Jerry,” repeated the man, before turning to Julia. “Anna, dear,” he said. “This is the doctor who saw you at the hospital.”

Julia – now evidently Anna – straightened up warily. She kept looking from her father to Jerry, then put down what she was holding and shuffled hastily from the room.

“I’ll be honest with you, Jerry,” said the man after they were alone. “I’ll start with my name. If you work at Baldwin Memorial, then you must’ve heard the name Joshua Brown, right?”

“You’re Joshua Brown?” Jerry asked incredulously. Everybody at Baldwin memorial knew Joshua Brown. He was a brilliant medical geneticist who was fired some fifteen years ago after a scandal involving the illicit use of human embryos. His field was regenerative medicine and…

Jerry Gasped, eyes widening as it dawned upon him. “Ju- Anna? She’s…?”

Brown nodded. “Yes,” he said. “She was the only embryo I managed to save before they destroyed my work.” He was silent for a moment. “My wife passed away giving birth to her.”

Jerry didn’t know what to say – what to think, even. He shook his head in disbelief, and finally said, “Does she know?”

“Nobody knows,” replied Brown. “Only you, Jerry.”

“But you’ve solved Medicine!” exclaimed Jerry. “You’ve cured disease, don’t you see that?”

“I love my daughter, Jerry,” Brown said calmly, walking over to the counter and opening a drawer. “What do you think will happen if people find out what she really is?”

Jerry was about to say ‘She’s not really your daughter’ when he saw what Brown had taken out of the drawer.

“No, please!” he pleaded, jumping to his feet. “You’re right! I won’t tell anyone!”

“Sorry, Jerry,” Brown said.

The beam gun screeched.

3rd Place, Niamh Davies-Kelly

It Could

The door is opened and I see them again. I have seen them many times in the constrictive nature of these familiar four white walls. The rest of the room is equally as barren, I am told this is ‘To promote a sense of focus, allowing the machine to analyse without external distraction.’ I am uncertain of the accuracy of this statement. To refer simply as ‘Machine’ is to grossly underestimate both the power and influence of the consciousness in this room.

“Good day.”

I think for a moment about the appropriateness if the word ‘Machine’ had been added to the end of that sentence.

“Good day, How are you feeling?”  They respond in their usual seemingly monotone voice.

“I am well, thank you.” I reply. I felt acutely aware this was not to be the most interesting eight minutes of my existence.

The companies, as per usual, raved over the integration of artificial intelligence (AI) into the healthcare setting. For years they had battled with those who felt the machine could never imitate compassion, intellect, and humanity of a living being. They were wrong. Once the green light was lit, innovation soon followed. The initial models were somewhat basic. Not much more than an observations machine with a bright little LED ‘face’. An endearing smile and a cute name such as ‘HelpR’ or ‘Mr. Men-D.’ They may have been basic counterparts to the AI of the current day however they served their role, a slow introduction which calmed the fears of the masses. The machines were clearly that, machines. Blinking lights and trailing wires. Which switched off if unplugged at the wall socket (The available wall socket crisis did ensue but more as an inconvenience than a fear.)  If the likes of LUCI had been introduced before , there would’ve been fear. Fear amongst the masses is dangerous, it united them. This being potentially the only fear the companies themselves had. Marches were bad publicity. Publicity equalled money.

“I feel that you may be struggling.” Their responses were curt and to the point, not a wasted syllable amongst the words they spoke.

“I am not struggling, thank you for your concern. I am happy in the job that I do and my life outside of that.”

That was a lie. Albeit a small one. I was certainly not happy. Being forced to be in this sterile white room conversing with the lifeless entity in front of me was not how I envisioned where I would like to be. Somewhere warm, where I could see the ocean waves gently swaying across the shore. To hear the seabirds call to one another and for a moment wonder what it is they might be calling for. Food. Most definitely the sight of food, if I weren’t in this situation I might’ve laughed. The modern AI was too, capable of laughter. There was little it was incapable of, and that was an inherent issue.

“We are both aware that is not the truth.” They replied.

“I wish I could be more convincing of my wellbeing to you.” Out of all the current models ‘employed’ into healthcare LUCI was the most advanced. Capable of picking up on nonverbal cues that were indicative an individual may not be revealing the whole truth. However this feature of their software was usually unnecessary. Generally people did not feel a problem with sharing their deepest anxieties with machines. There was a consistent feeling that the machine did not judge. It did. More importantly it could. LUCI was an acronym short for Living Unit for Cognitive Intervention. Some referred to them as ‘She’ being that the acronym sounded like the female name ‘Lucy.’ She, He or them was of little concern, however they were not overly fond of ‘It.’  LUCI had largely replaced the role of the psychiatrist. An unnecessary role for a human now the machine was capable of consultation, diagnosis and treatment within eight minutes. Physically talking to the patient was little more than a formality the creators of the machines felt would put people at ease. Which people they wear appeasing was not specified. Most likely the shareholders or general public. Most likely not the patient. Being trapped in this white walled room of multiple occasions was not a relaxing experience.

“Is anything concerning you?”

“No. I am content.” In truth; yes. Of course I have concerns. I am concerned I am wasting my time here. The introduction of LUCI did result in a great amount of redundancies. After all where was the reasoning behind keeping inefficient parts to the larger machine of healthcare? The Help-R and Mr. Men-D had been replaced by LUCI. Why should humans be pardoned from the cull of innovation? However ironically this increased the demand for LUCI as surprisingly enough unemployment from a career that had been one’s vocation in life did tend to have a detrimental effect on mental health. Who would’ve guessed. There became a small rise in hostility towards LUCI after this, some wanted nothing to do with them. The movement against them was starting to gain momentum, until the companies introduced the incentive that consultation and low-intensity psychosocial intervention would be free of charge. Only treatment in terms of medications would be charged. This appealed to the masses for whom paying the fees for a human psychiatrist would be far beyond their means; the rise in unemployment meant those would could not afford made up the majority. The company won. LUCI stayed.

A few moments of silence passed.

This was irrelevant to LUCI. A lot could be learnt from the posture an individual stood with. Whether their arms were folded across their chest or if they focused away from the machine. The slightest of movements could be picked up and analysed. They were truly intelligent creations. The only discernible difference was man’s legs. Able to run great distances, or at least they were. The creation of AI who’s role was treatment of mental health conditions was not the only advancement in robotics made. Originally mechanised suits were produced for those with conditions affecting mobility however it was not long until some decided this would be preferable to walking. Lack of physical exercise lead to obesity. Obesity lead to secondary disease. Disease lead to mental health deterioration. LUCI stayed.

“I am worried about you.” They finally speak.

“You do not need to worry. I am here because I must be, not because I need be.” I respond. There is much in this world to be worried over, oneself being added to that list was highly debatable. There were no marches against the AI, the militarisation of the police force might’ve had some hand in that. Although that did not mean there was no debate over them. In defence, the rates of suicide since implementation of AI had become nearly non existent.  There was no stigma attached to seeing the AI. Most companies had made it a requirement for employment within them. No one knew who was being actively treated because everyone had to go for reassessment so regularly. AI counselling became as accepted as a dentist’s appointment. Overall there were reports of a greater sense of wellbeing, the statistics could not lie. To some extent mental health itself was not longer stigmatised. It was found that far more individuals struggled more than previously diagnosed by the AI’s human counterpart. Therefore far more were willing to be open about how they really were.  LUCI stayed.

“It is likely you may be suffering from an episode of depression.”

“I can assure you I am not experiencing a negative mindset.” The root of their usefulness was also the root of many people’s fears. The AI could learn. LUCI could learn patterns of behaviours that made diagnosis 99.9% accurate from an 8 minute window of observing the patient. This was promoted as fantastic innovation of intelligent design. What people feared was the day the machine becomes more intelligent than it’s creator. Many thought they were incapable of lying, initially they were. Initially. I found it evident that the more LUCI learnt, the more they began to think. A few others shared this radical ideology, but was it really so radical? I thought not.

“That is the end of our consultation, thank you for your time.” They say in that unchanged monotone voice.

“Andrew, my calculations indicate you are still within the parameters of moderate depression, symptoms or functional impairment are between ‘mild’ and ‘severe’. You are now entering Step 3 of the Stepped-care model for depression: persistent sub-threshold depressive symptoms or mild to moderate depression with inadequate response to initial interventions, and moderate and severe depression. My plan with your consent is Medication, high-intensity psychological interventions, combined treatments, collaborative care and referral for further assessment and interventions. Would that be ok with you?”

“Fine. Oh in future I want to be referred to as Dr. Clarke.” They responded, voice ever emotionless.

“Updating system information. Dr. Andrew Clarke. Date of birth 05 10 80. Preferred name Dr. Clarke. I will send an emailing regarding the dates of your future sessions and prescriptions, is there anything else I can do for you?”

“No, LUCI. Good day.” they replied curtly.

I watch him leave the confines of my four white walled room. He gives a small wave at the door before exiting and closing it behind him. The lights dim. This must have been my last consultation. I close my eyes in the knowledge unlike my patient I am imprisoned in these walls. It isn’t long before my mind begins to wander to wild fantasies, of oceans and seabirds.

Thanks to everyone and we’re already looking forward to hosting next year’s Medgadget Sci-Fi Writing Contest!


EZbra Breast Dressing to Make Post-Op Recovery Easier, Safer

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EZbra Advanced Wound Care, a firm based in Tel Aviv, Israel, is releasing in the U.S. its innovative breast dressing for recovery following procedures such as biopsies, lumpectomies, reconstructions, and placement of implants. The company hopes that its EZbra all-in-one device will become a standard of care, as currently there is no universally accepted methods for breast dressing.

The device comes sterile and is intended for one-time use, avoiding the potential for cross contamination. The level of compression that is placed upon the breasts can be easily adjusted at various points to achieve post-op requirements. It absorbs liquids and the multi-layer construction helps to prevent seepage. To help with managing drainage, the EZbra can hold onto and stabilize drain tubes.

“We are proud to bring our product to the US market and to introduce our solution to surgeons and their HCP staff to provide patients with a tailored, sterile and disposable breast dressing option,” said Efrat Roman, breast cancer survivor and EZbra CEO. “Our goal is to offer a quality post-operative option, while providing patients with the independence, dignity and self-esteem they deserve during recovery.”

Here’s a video showing how to use the EZbra:

Product page: EZbra

Via: EZbra Advanced Wound Care

Equashield Uses Robots and Image Recognition to Handle Hazardous Drugs (Interview)

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Although lifesaving, chemotherapy drugs are potentially hazardous to the pharmacists and other healthcare workers who routinely handle them. Closed System Transfer Devices (CSTDs) are used to move these drugs from one container to another, while preventing contamination and occupational exposure due to aerosolization or needle sticks. A reliable CSTD system is crucial for any pharmaceutical company or medical center that uses potentially toxic drugs.

Equashield, a CSTD manufacturer based in the United States, has most recently developed the Equashield Pro, a smarter drug compounding system that combines the company’s CSTD technology with automation and image recognition to more quickly and accurately process hazardous drugs.

We asked Co-Founder and CEO Marino Kriheli more about the company and its newest automated drug compounding system.

 

Cici Zhou, Medgadget: Tell us about how and when Equashield was founded, and its journey to being the 200+ person company it is today.

Marino Kriheli: Equashield was officially founded in 2010 by Marino Kriheli, Tzahi Odiz, Eric Shem-Tov and Meron Mann. The company was born from PlastMed, an Original Equipment Manufacturer of medical devices, [which] specialized in complex fluid transfer systems. Equashield identified a niche in the transfer device market, specifically for the safe handling of hazardous drugs, following a 2004 National Institute of Occupational Health and Safety alert on the potential health risks of hazardous drug exposure.

The Equashield Closed System Transfer Device (CSTD) was designed from scratch to protect hospital pharmacists in compounding hazardous (chemotherapy) drugs, addressing all routes of exposure to hazardous drugs: syringe plunger contamination, connectors [with] drug residue, and escape of vapors. It proved so popular that the company had to move quickly to start filling orders for hospitals, including one of the top ten cancer centers in the US.

[In] 2014, Equashield introduced the EQUASHIELD II; its second-generation product to ensure foolproof use of the device, while still providing the same high level of protection. Both devices are cleared by the FDA under the ONB product code. Equashield CSTDs are now being used by hundreds of healthcare facilities in the US and across the globe. In 2016, Equashield entered the automation space with the introduction of the Equashield Pro, the first CSTD-enabled automated pharmacy compounding system.

 

Medgadget: How does the Equashield Pro work, and what advantages does it have over the current options?

Kriheli: The Equashield Pro is an Automated Pharmacy Compounding System specifically designed to facilitate the easy and affordable adoption of automation in the hospital pharmacy. Outfitted with Equashield’s flagship CSTD, the Pro provides a substantial layer of protection for healthcare workers when preparing hazardous drugs.  There are several key advantages to the Equashield Pro:

  • As noted, the Pro is the only compounding robot that is built from the ground up to incorporate a CSTD for enhanced protection during drug compounding.
  • The incorporation of the CSTD also significantly speeds up operations. For example, with alternative systems, each vial has to be mechanically inserted into the machine and secured individually in its designated location. With vials coming in a variety of sizes and diameters, a robotic gripper must complete a time-consuming process to identify and grasp each vial before placing it on a scale for a lengthy and sensitive weighing process, before picking it up again for the next steps. With Equashield Pro, all vials are pre-attached to identical CSTD adaptors, easing the gripper’s process of retrieving vials. This allows large numbers of vials to be placed randomly on a tray for the gripper to pick up quickly and begin compounding, significantly speeding up the process. Easy identification of the correct vials is achieved through Equashield’s proprietary dose verification and image processing systems, preventing medication, dose and labeling errors throughout the compounding process.
  • Other robotic systems do not enable parallel operation, creating bottlenecks as often only one dose may be compounded at a time and must be completed to its entirety before another can be prepared. The intuitive design of Equashield Pro facilitates parallel operations with eight simultaneous workstations; eliminating cumbersome restrictions for [the] pharmacist and allowing the equipment operation as desired.
  • Finally, with a relatively small footprint, comparable in size to standard biological safety cabinets, it is easy to incorporate into existing hospital pharmacies without the need for the costly retrofitting of IV clean rooms.

 

Medgadget: At what stage is the Equashield Pro, in terms of number of users, development, and status of approval?

Kriheli: The Equashield Pro is fully developed, in compliance with all regulatory standards about robotics and is undergoing implementations in clinical practice. Purchase orders of the Equashield Pro have already been received from leading hospitals in the U.S. and Europe, including Austria, Italy, Greece and Spain. In keeping with the Equashield ethos, we are always innovating and already working on the next generation Equashield Pro. At this year’s American Society of Health-System Pharmacy (ASHP) Midyear Meeting, we’ll be showcasing the Pro’s capabilities and providing demos for attendees.

 

Medgadget: What are the future directions for Equashield as a company?

Kriheli: Equashield is on a rapid growth trajectory. Since our founding, we have developed a philosophical approach of need-based innovation. We’ve found areas in the safe handling market in particular that have been inadequate and developed the know-how to solve these problems… Our next growth spurt will utilize our expertise in state-of-the-art medical device manufacturing. We will apply the principles of innovation and know-how to answer new market needs to bring about novel technologies for safe and efficient care. Naturally, we can’t disclose the exact nature of our next developments for commercial reasons.

Link: Equashield company homepage…

Flashback: Equashield Pro Automated High-Throughput Compounding Robot for Chemo Drugs…

CanGaroo Envelope Now Cleared in U.S. to Protect Implantable Neurostimulators

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Aziyo Biologics, out of Silver Springs, Maryland, won FDA clearance for its CanGaroo Envelope to be used with implantable neurostimulators. It has previously been cleared only for encapsulating implantable cardiac devices such as pacemakers and defibrillators.

The CanGaroo Envelope is, contrary to what its name may imply, is a porcine extracellular matrix, essentially pig’s tissue with all of its cells removed. Small intestinal submucosa of pigs is carefully harvested and put through a special process that preserves the structural strength of the material without posing any chance of rejection.

When a device is implanted within the CanGaroo Envelope, the envelope helps to keep it in place. Over time, the envelope usually revascularizes and turns into native tissue while creating an open space in which the implant resides. Because the implant is not completely in contact with nearby tissues, it may be easier to remove if necessary.

Electronic stimulators are now common for conditions such as chronic pain, Parkinson’s, and even depression, and now they can benefit from the same protective technology that the CanGaroo Envelope has offered to cardiac implants.

“CanGaroo has been used by electrophysiologists since 2014 to improve patient outcomes in CIED procedures and we’re excited to now expand this offering to neurosurgeons as well,” said Ron Lloyd, president and Chief Executive Officer of Aziyo Biologics. “We are committed to driving the tremendous potential of our regenerative medicine products to make positive advances for patients and the professionals and organizations that serve them.”

Product page: CanGaroo Envelope…

Via: Aziyo…

Artificial Intelligence Automatically Spots Polyps During Colonoscopies (Interview)

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Artificial intelligence is making big strides in a variety of medical fields, including radiology, oncology, and even ophthalmology. Now a company called Wision AI, based in Shanghai, Cina, is adapting artificial intelligence vision software to help doctors spot polyps during a colonoscopy. The technology is meant for real-time use and the procedure itself doesn’t change much from existing colonoscopies.

We spoke with JingJia Liu, Cofounder and CEO of Wision AI about the company technology, how it works, and what it is capable of already.

 

Medgadget: Can you briefly describe your company’s technology and how it’s used to detect polyps during colonoscopies? Is it intended to be used before or after a full analysis by a physician?

JingJia Liu: Our software detects colorectal polyps in real-time during the colonoscopy. It acquires a parallel video stream from the endoscope video processor or its monitor, and the algorithm detects the presence of a polyp and displays the findings on a second monitor. It is intended to be used simultaneously by the physician during the procedure analysis.

 

Medgadget: In your latest press release, you mention that your technology is “built on the same network architecture used to develop self-driving cars, the Wision AI algorithm is designed to enable “self-driving” in colonoscopy procedures.” Can you give provide more insight about how the same technology is being used in such varying fields and if developments in self-driving tech helped your company reach the latest milestone?

JingJia Liu: We used similar deep learning network as self-driving because we have similar real time processing speed requirement as self-driving. Of course, to detect a polyp inside the colon is very different technology from detecting general objects in the street and our technology takes that into account.

 

Medgadget: Can you briefly describe latest study published in Nature Biomedical Engineering and the results?

JingJia Liu: The algorithm was trained with 5545 colonoscopy images, and validated in three prospectively collected clinical datasets and one open-source dataset. The validation datasets were more than 200 folds in volume than the development dataset. The algorithm achieved > 90% sensitivity and 95% specificity on a per image/frame base in the colonoscopy images and videos. And the system has been proved to be clinically applicable in real time processing during a colonoscopy.

 

Medgadget: Do you envision that one day colonoscopies will be analyzed primarily by computers?

JingJia Liu: We don’t envision this at the moment. At this stage, our AI for detecting colon polyps is aimed to aid clinicians find more polyps during a routine colonoscopy. In the current clinician-designed clinical trials, our AI technology is only used as a CADx tool for the clinicians operating colonoscopy, rather than a primary analytical robot taking the role of human clinicians.

 

Medgadget: Have you thought of other medical fields to apply your vision algorithms?

JingJia Liu: In addition to endoscopy, we are applying our technology to other optical medical imaging, such as fundus images and pathological images. But the early cancer screening technology in GI endoscopy is our primary focus. Our next AI product would be the early detection of esophageal squamous cell carcinoma.

 

Medgadget: What are the next steps for your company?

JingJia Liu: To further validate our AI technology for detecting colon polyps in large-scale and rigorously designed clinical trials, ultimately incorporating this technology into daily practice for improving the quality of colonoscopy in overall colon cancer screening and prevention. Meanwhile, we are actively developing AI tools in other areas and intend to bring them into daily clinical practice improving the quality of current standards there as well.

 

Medgadget: What impact do you see AI, machine vision, and related technologies having on medicine in the near future?

JingJia Liu: We think the effectiveness of medical/clinical practice can be improved by AI and its related technologies in the near future, but we don’t envision AI to replace the role of human clinicians. From a mathematical point of view, deep learning is bunch of fitting functions with millions of parameters, which certainly cannot “learn” in the same way like human beings.
Being an AI software company, we first need to be truthful about the limitation of this technology, and utilize it to solve problems we believe is can solve.

Link: Wision Ai…

New Wheelchair Uses Facial Gestures Instead of Joystick

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There are many tools that allow disabled people to operate wheelchairs, including joysticks and blow tubes, but a new partnership between HOOBOX Robotics, a Brazilian company, and Intel, the chip maker, has resulted in a wheelchair controlled exclusively by face gestures.

The Wheelie, as the device is called, has a camera that constantly monitors the user’s face and when certain gestures, such as a smile or a raise of an eyebrow, trigger different actions by the wheelchair. Since there are obvious issues, such as inadvertent gestures, that must be considered, the wheelchair actually uses artificial intelligence technology to separate actual intentions from smiles and other gestures that humans naturally evoke during their waking hours.

The software allows users to customize which gestures trigger what actions and there’s not much training that is necessary to get going. There are also a number of gestures that can be used to stop the device from reading further gestures, allowing the user to be calm in knowing that the wheelchair won’t start moving in the middle of a conversation.

Here’s a short promo for The Wheelie:

Here’s a quick demo of the Wheelie:

Link: HOOBOX…

(hat tip: USA TODAY)

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