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AI-enabled cancer screening platform Ezra snags $4M in seed funding

AI-enabled cancer screening platform Ezra snags $4M in seed funding | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Last week New York-based, AI-powered cancer screening platform Ezra announced that it scored $4 million in a seed funding led by Accomplice, with additional funding from Founders Future, Credo Ventures, Seedcamp, Esther Dyson and various unnamed startup founders and angel investors.

This funding announcement is paired with the beta launch of its prostate cancer screening program. Right now the technology is available in beta at RadNet’s Lenox Hill Radiology facility in Manhattan, but is available by invite only.

The company said that it is working on designing an technology that uses MRI scans to help radiologists with their diagnoses. That technology has yet to receive the FDA nod, as the company is currently planning on going to the agency in 2019.

In the meantime, Ezra's service is employing board-certified radiologists to analyze its MRI scans. According to a statement released by the company, this technique offers a noninvasive way to detect cancer early, but in a noninvasive way.

Why it matters

Each year there are 164,690 new cases of prostate cancer in America, according to the American Cancer Society. In fact, the society says, one in nine men will be diagnosed with the disease during his lifetime, impacting older men and black men at a higher rate.

However survival rates for prostate cancer are high; for patients with local or regional stage prostate cancer the survival rate is nearly 100 percent, according to the society. But that rate plummets to 29 percent for patients with distant stage cancer, meaning the cancer has spread into their distant lymph nodes, bones or other organs.

“We should all check our bodies for cancer as part of our routine health regimen. To make that possible, we’re aiming to combine a better patient experience with the most advanced medical imaging technology and the Ezra AI. Our goal is to improve the speed, accuracy and affordability of cancer screening,” Emi Gal, CEO and cofounder of Ezra, said in a statement.
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AI Healthcare Innovations in Europe - An Overview of Startups and Innovation

AI Healthcare Innovations in Europe - An Overview of Startups and Innovation | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Accenture forecasts that growth in the AI healthcare market is expected to reach $6.6 billion by 2021 from $600 million in 2014, growing at an annual compound rate of 40%. We’ve covered AI in healthcare extensively on TechEmergence, but in this report we’ll be looking at four European companies offering more niche solutions for both business and consumers in the healthcare space. We found that these solutions are intended to help CPG companies with at least one of the following business problems:

- Providing information on symptoms
- Fertility awareness
- Prioritizing patient care
- Genetic testing

What Business Leaders in Europe’s Healthcare Industry Should Know

All of the companies listed in this report are supported by PhD-level talent in hard science, which is the most important trust signal we look for when determining the legitimacy of a company’s AI software. Interestingly, however, none of these executives hold computer science or related degrees.

It’s possible that this indicates a greater need for subject matter expertise when it comes to building AI software for healthcare than for other industries. Oftentimes in industries such as insurance and banking, the CTO or executive in charge of building the machine learning model behind the software their companies offer holds a degree in machine learning or computer science generally.

In the case of healthcare, we’ve found that degrees in biology, medicine, or physics are much more common. Elina Berglund Scherwitzl, co-founder and CTO of Natural Cycles, probably exemplifies this the most: she was part of the team that discovered the Higgs Boson. We have a high level of confidence in these AI healthcare innovations due to the talent behind them.

Blueprint Genetics seems to have the most niche use case, claiming to offer a software that analyzes patient DNA in order to determine the likelihood that genetic conditions will show up in various generations of the patient’s lineage. The company seems to sell their software to hospitals and healthcare providers looking to provide better care to their patients by arming them with information about their and their childrens’ risk of genetic disorders.

Siemens Healthineers also sells to hospitals. The company offers a software that it claims can help hospital personnel prioritize patients based on the discrepancy between the care they are receiving and the hospital’s own care guidelines.

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‘Machine doctor’-patient collabo: Using ePRO data in AI to improve personalised healthcare

‘Machine doctor’-patient collabo: Using ePRO data in AI to improve personalised healthcare | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
First proposed by Professor John McCarthy in 1956, Artificial Intelligence (AI) has become a common topic in the healthcare industry. In any case, the push toward AI in the healthcare industry is still in its early stages. As we hope to streamline patient care and reduce expanding costs, we are obliged to consider the use of data science to address these problems because they will not go away. Artificial intelligence promises to drastically change healthcare, however, without data, it is useless. With AI revolutionising healthcare, it should remain clear that the patient is the priority and should be able to contribute to the data that is fed into the algorithms for analysis and prediction. Today, mHealth technologies enable patients to record vital data outside of traditional care environments that can help to expand the continuity of data available to improve healthcare and outcomes. This way, AI can analyse these personalised datasets leading to better treatment and outcomes. As a result, AI will boost personalised medicine.


The potential of Electronic Patient-Reported Outcomes (ePRO) in AI

ePRO, as the name suggests, are patient-reported outcomes that are collected electronically. The primary desire of using AI in the healthcare industry is to analyse the relationships between prevention or treatment methods and patient outcomes (Coiera, E. (1997). The collection of patient-reported outcomes attracts attention to issues of significance to patients —physical function and quality of life. The integration of ePRO data into clinical decisions requires the insightful structure of user-friendly interfaces that consider patient experience and show personalised data in ways to improve patient care (Andrea L. Hartzler 2015). Fusing the patient point of view into AI offers the potential to improve outcomes and quality of care. Additionally, ePRO is vital for learning health care systems and patient-focused outcomes research that evaluate the effectiveness of treatments (Abernethy AP et al. 2010).

There’s no doubt that we have made extraordinary progress in our innovative capacities, however, actually, we are merely beginning. We have figured out how to produce many unique datasets, yet the primary challenge is incorporating various data sources and use them for insights. Combining population-level data sets, like Electronic Health Records and ePRO could produce better predictive and prescriptive tools than either alone. These data sources utilised individually have delivered real progress that guide the treatment and prevention interventions, yet the joined power could additionally improve our capacity to unravel patterns that could inform and prompt new thoughts on best disease management practices. For researchers, a single app like Teamscope combining Electronic Data Capture (EDC) and ePRO could reduce the burden of managing clinical trials by decreasing the time and cost of patient recruitment.

As a matter of fact, many patients already use mobile technology to track their well-being outside of the traditional clinical setting. From smartphones to wearables that can track a heartbeat nonstop or your steps, health-related data can be generated on the go. ePRO data can inform on deteriorating signs, medication noncompliance and also act as a risk predictor.

“There’s a very good chance wearable data will have a major impact because our care is very episodic and the data we collect is very coarse. By continuously collecting granular data, there’s a greater likelihood that the data will help us take better care of patients.” - Omar Arnaout, MD, Computation Neuroscience

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OTC drugmakers face an uphill battle on Amazon. But they should still be there, expert says

OTC drugmakers face an uphill battle on Amazon. But they should still be there, expert says | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Amazon is now the third-largest digital ad platform, but pharma marketers are mostly shut out. That’s because most of Amazon’s ads are for products sold by retailers, and of course, prescription drugs can't be purchased that way.

At least, not yet. Amazon continues to show interest in healthcare in general and in the pharmacy and prescription drug delivery business, specifically. In June, it bought online independent pharmacy PillPack, which analysts cast as “the tip of the iceberg” for Amazon’s plans in healthcare.

Still, even as Amazon looks for an Rx entry, it's already launched its own Basic Care OTC medicine lineup. Pharma marketers with OTC brands should be figuring out their own strategies for Amazon, said Wes MacLaggan, senior vice president of marketing at ad management platform Marin Software, which works with OTC drugmakers including Pfizer and GlaxoSmithKline on optimizing advertising on search, social and e-commerce channels.

Over-the-counter remedies, which are part of many of Big Pharma's consumer divisions, are burgeoning on Amazon, so much so that Amazon quietly launched its own Basic Care brand line of OTC products last year, made by private-label manufacturer Perrigo.

What's an OTC player to do? There are two typical Amazon advertising choices: sponsored brand ads or sponsored product ads. Sponsored brand ads appear much like a banner ad at the top of the page with a “Sponsored By” label beside the brand, for example Advil or Vicks, followed by two or three of each one's specific products that can be clicked on to buy.

The next ad form is sponsored product ads, which appear in the row just below the sponsored product banner ad on the Amazon search results page. Those ads are for single products in a line, each one boxed and containing the word “sponsored” so that shoppers know the ads are paid. Sponsored product ads work much like keyword buys on search giant Google, where OTC companies bid on specific health-related or symptom words and the ones with the highest bids appear first.

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Amazon In Healthcare: The E-Commerce Giant's Strategy For A $3 Trillion Market

Amazon In Healthcare: The E-Commerce Giant's Strategy For A $3 Trillion Market | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Amazon could use its expertise to disrupt everything from the pharmaceutical supply chain to Medicare management. We break down the healthcare areas best suited for an Amazon entrance.
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Amazon is looking to dominate more than just online retail.

The e-commerce behemoth is serious about entering healthcare, bringing with it a non-traditional business model, infrastructure in logistics & computing, and customer love.

Many existing health giants are scrambling to compete, while others are looking for ways to Amazon-proof themselves.

But this isn’t Amazon’s first attempt at transforming the space.

Between 1999-2000, the company began investing money into Drugstore.com with plans to expand its e-commerce business into the pharmacy space. It eventually ran into the existing web of middlemen, regulators, and more, which brought its ambitions to a halt.

Now, Amazon is trying again. Earlier this year, it announced a joint healthcare venture with JPMorgan Chase and Berkshire Hathaway. Before the collaboration, the company acquired online pharmacy PillPack for nearly $1B.

But it’s not the only tech company expanding into healthcare.

Many are advancing in the space by playing to their strengths: Apple’s patient-centric vision prioritizes consumers, while Google continues to apply AI to everything from medical devices to lifestyle management solutions. Microsoft is building health data management on top of its cloud platform Azure.

In our Healthcare 2025 research briefing, we asked which tech giant would have the biggest impact on healthcare. Even before announcing any concrete plans, Amazon came in second place — just behind Google.

But as the e-commerce giant moves into the healthcare sector, many questions arise:

What strategies does the company plan to use to enter new target verticals, especially those with established leaders in the space?
Which companies are most at-risk for an Amazon entrance? What business models will become obsolete if Amazon chooses to enter the space?
Will Amazon’s advantages — which have worked well in areas such as retail — translate across healthcare, or is the company out of its element?
Is the timing right? What factors today will enable Amazon to succeed in healthcare?

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L’interface cerveau-ordinateur, efficace dans le traitement de diverses pathologies neurologiques

L’interface cerveau-ordinateur, efficace dans le traitement de diverses pathologies neurologiques | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Soigner à domicile et sans médicament des pathologies neurologiques chroniques telles que les troubles de l’attention chez l’enfant, les douleurs chroniques ou encore les séquelles d’AVC ou la dépression, tel est l’objectif de la société Mensia Technologies, qui développe depuis quelques années avec succès des dispositifs médicaux basés sur le neurofeedback.

Il s’agit d’une technique qui permet d'apprendre à contrôler directement son activité cérébrale grâce à un retour (feedback), le plus souvent visuel, sur cette activité mesurée en temps réel. Concrètement, l’activité cérébrale est enregistrée grâce à un casque à électrodes similaire à celui utilisé pour l'électroencéphalographie (EEG). Un ordinateur traite, en temps réel, les signaux EEG, en extrait des informations sur l’activité du cerveau, et les convertit en un retour visuel (ou auditif), qui varie donc avec le signal physiologique.

Cette technologie s’est concrétisée en 2018 avec la commercialisation de Mensia Koala, premier traitement non médicamenteux des troubles de l'hyperactivité de l'enfant. Il est le fruit de l’association, en 2016, de Mensia Technologies, une start up spécialisée dans les thérapies digitales dans le domaine des pathologies neuropsychologiques chroniques et de l’Institut national de recherche en informatique et en automatique (Inria). Les chercheurs ont utilisé et développé pour un usage médical le logiciel OpenViBE (OpenViBE 2.0), l’un des principaux outils dans le domaine de l’interface cerveau-ordinateur.
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Bientôt des usines à la pointe du numérique chez Sanofi

Bientôt des usines à la pointe du numérique chez Sanofi | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Les technologies avancent à grand pas et Sanofi n'entend pas être à la traîne. Le laboratoire pharmaceutique a décidé de convertir ses 75 usines du monde entier au numérique. Un objectif qui devrait être atteint d’ici à 2021.

Et l'entreprise compte bien y mettre le prix. Pour y arriver, Sanofi compte investir 60 millions d’euros sur la période, soit environ 20 millions d’euros chaque année. Capteurs connectés, intelligence artificielle, maintenance prédictive, tous ces outils intègreront bientôt les usines traditionnelles, si bien qu’après transformation, toute la chaîne de production pourra être observée en temps réel.
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Epilepsie : un brassard connecté pour détecter les crises nocturnes

Epilepsie : un brassard connecté pour détecter les crises nocturnes | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Une nouvelle étude montre que le « NightWatch », un brassard connecté, détecte 85 % des crises d'épilepsie nocturnes. L'appareil a été créé par un consortium d'institutions académiques néerlandaises.

L'épilepsie touche près de 60 millions de personnes dans le monde, et 600 000 personnes en France dont près de la moitié sont âgées de moins de 20 ans, d'après les chiffres de l'Inserm. Derrière la migraine et les démences, cette pathologie constitue la troisième maladie neurologique la plus fréquente. Si les symptômes sont nombreux et varient selon les individus, les plus spectaculaires restent les fameuses crises qui se manifestent par des convulsions, des absences ou de la rigidité musculaire.

Et ces crises d'épilepsie peuvent être particulièrement dangereuses la nuit, notamment si aucun témoin n'est présent. Il est possible, lors d'une convulsion, de tomber et de se blesser au sol ou encore de s'asphyxier dans le lit. Si de tels cas sont rares, le risque de mourir de telles crises est supérieur chez des malades handicapés, puisqu'il serait de 20 %. Des chercheurs ont donc testé un brassard, appelé NightWatch, capable de détecter différents types de crises. Il a été créé par un consortium néerlandais regroupant le centre d'épilepsie Kempenhaeghe, l'Université de technologie d'Eindhoven, la Fondation pour les institutions de l'épilepsie aux Pays-Bas, le Fonds pour l'épilepsie et des représentants de patients et sera commercialisé par LivAssured. Les résultats scientifiques ont été révélés dans un article publié dans la revue Neurology le mois dernier.
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Electronic Tattoos Add Power to Wearable Computing

Electronic Tattoos Add Power to Wearable Computing | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Researchers from Carnegie Mellon University's College of Engineering and the Institute of Systems and Robotics at the University of Coimbra, Portugal, have developed a simple, efficient method to make robust, highly flexible, tattoo-like circuits for use in wearable computing.

The low-cost process adds a trace of an electrically conductive, liquid metal alloy to tattoo paper that adheres to human skin. These ultrathin tattoos can be applied easily with water, the same way one would apply a child's decorative tattoo with a damp sponge.

Other tattoo-like electronics either require complex fabrication techniques inside a cleanroom or lack the material required for stretchable digital circuit functionality on skin.

Carmel Majidi, an associate professor of mechanical engineering and director of CMU's Soft Machines Lab , and Mahmoud Tavakoli, director of the Soft and Printed Microelectronics Laboratory at the University of Coimbra, partnered to develop methods for direct printing of stretchable electronic circuits. The tattoos are being developed under the Strechtonics project, one of the Entrepreneurial Research Initiatives of the Carnegie Mellon-Portugal Program, funded by the Fundação para a Ciência Tecnologia (FCT) and coordinated by Professor Aníbal Traça de Almeida.
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Diabetes patients want more information about research  #esante #hcsmeufr #digitalhealth

Diabetes patients want more information about research  #esante #hcsmeufr #digitalhealth | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
People affected with diabetes want information on research and innovation to be distributed through social media; not just information about what they should eat or how to inject insulin.
 

In cooperation with the Norwegian Diabetes Association, Elia Gabarron, a researcher at the Norwegian Centre for E-health Research, is conducting research on the use of social media for diabetes.

 

Research shows that the wellbeing of people affected with diabetes improves and that they greatly benefit from information about the disease on social media. Gabarron carried out a systematic review, which shows that people with diabetes might feel better after receiving support or relevant information about the disease on social media platforms.

 

She wanted to use this as a starting point for further research. In the new research project ‘Social Media for Health Promotion in Diabetes’ she looks at how the Norwegian Diabetes Association can use platforms, such as Facebook, Instagram and Twitter to distribute information to their members.

 

“We came up with the idea of using social media platforms to provide diabetes patients with the contents they would like to find, as my earlier research shows they greatly appreciate this,” says Gabarron.

 


Via Plus91, Lionel Reichardt / le Pharmageek
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Top 8 Healthcare Predictions for 2019

Top 8 Healthcare Predictions for 2019 | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
What can you look forward to in healthcare in 2019? The debate expects to get hotter between AI vs. Physicians, Consumer vs. Clinical, Human empathy vs. Machine Intelligence as many new players enter the ecosystem

We have been writing the predictions for healthcare every year now for the past 10 years. We also review back how we did each year and each year we are getting to be more accurate. The 2018 predictions that were released in December 2017 were almost 98% accurate and each one of them panned out during the course of the year.

Top 8 Healthcare Predictions for 2019Frost & Sullivan

Globally, 2019 will be a year of value-based care as we expect the ‘outcomes-based care’ focus to globalize. This will trigger maturation of risk-sharing in solution contracting between providers and drug/device original equipment manufacturers (OEMs), driving business value for providers. Furthermore, access to affordable and quality care will be key political agendas for upcoming 2019 elections in emerging markets such as Asia, Africa and, Central and Eastern European countries. As the lines between retail, IT and healthcare industries continue to blur, during 2019, Google, Apple, Facebook and Amazon (GAFA) in the West, and Baidu, Ali Health, Tencent (BAT) in East will start to dominate the Individual Care space. Non-traditional digital marketplace providers such as Ali Health, Tencent, Amazon, Google, Apple, Microsoft, and IBM among other will dominate the home health space, providing the required impetus to public health systems to ensure accessibility and affordability of care. We also anticipate future drugs and devices R&D investments will be more targeted to meet the unique needs of emerging markets in Asia. Finally, we anticipate 2019 will be a reality check for two of the most hyped technologies for healthcare of this decade, viz. artificial intelligence (AI) and blockchain.
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AI holds great promise for visual fields like dermatology, but faces many challenges

AI holds great promise for visual fields like dermatology, but faces many challenges | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Computer vision has great promise for helping to democratize fields like wound care, dermatology and more. However, as companies explore this potential, they’re also discovering a number of challenges to overcome.

The data problem

“Getting the data is really the biggest challenge, not the AI,” Karen Panetta, IEEE fellow and dean of graduate engineering at Tufts University who studies AI use cases in healthcare, told MobiHealthNews in an interview earlier this year. “We’ve already got the models, we just need more training data to validate this expertise. And then, again, getting doctors to also validate, to get random things from a cellphone, and you want multiple doctors to do it because they have to agree.”

There are existing clinical data sets, but the pictures they contain are clinical images, taken in controlled conditions, often with a dermascope, which is a specialized medical instrument for taking pictures of the skin.

Furthermore, getting access to medical datasets is very difficult, since patients have to have consented to have their data used in research and most have not. Even if they have, the researchers have to secure IRB approval for access to the images.

Mary Sun is a medical student at the Icahn School of Medicine at Mount Sinai Medical Center in New York, but she’s also working remotely with teledermatology company First Derm on improving the company’s AI algorithms. She says a traditional clinical research approach doesn’t bring in anything near the scale needed for machine learning.

“The issue in general is that a lot of the data people are pulling in from healthcare studies, the enrollment process for clinical trials is generally very slow, and very manual. Not that this is specific to any one institution, but if you have sample sizes in the low hundreds or not even 100 — and there are plenty of studies that are 30, 50, 70 participants, just because it’s so difficult to get a willing cohort that will show up for all the testing you need, and generally you do recruitment locally so it’s just the patient population that’s available to you and so on and so forth— and that’s problematic, right? … The whole point of a classifier is to be generalizable across a population, and you’re limited to a small amount of data, that already is an issue from a statistical standpoint.”
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Santé : des chercheurs mettent au point une intelligence artificielle diagnostiquant les lésions rénales

Santé : des chercheurs mettent au point une intelligence artificielle diagnostiquant les lésions rénales | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Des chercheurs ont mis au point une IA capable d’évaluer le risque de lésions rénales aiguës à partir de notes cliniques. Celle-ci prédit les risques de développer une telle pathologie dans les 24 heures.


Une IA qui prédit les risques d’apparition de lésions rénales aiguës

Des chercheurs de la Northwestern University et du Health Science Center de l’Université du Texas ont mis au point une intelligence artificielle capable de prédire le développement de lésions rénales aiguës dans les 24 heures auprès des patients placés en soins intensifs.

Les lésions rénales aiguës sont une affection dans laquelle les reins ne parviennent plus à filtrer les déchets du sang. Cela peut conduire à une destruction du système rénal du patient. Le taux de mortalité d’une telle pathologie s’approche des 89 % s’il dépasse le stade 2 (sur les 3 étapes de l’affection). Le risque de décès est multiplié par douze si la pathologie apparaît après une chirurgie abdominale majeure.


Désormais, les praticiens vont pouvoir s’appuyer sur une intelligence artificielle mise au point par des chercheurs texans. Cette IA est capable de collecter et d’extraire les facteurs de risque des données électroniques des dossiers des patients et de prédire la probabilité d’apparition de lésions rénales aiguës dans les 24 heures suivantes. Cette intelligence artificielle pourrait ainsi avertir les médecins des risques d’apparition de la pathologie peu de temps après l’entrée en soins intensifs du patient.

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AI-powered kidney disease diagnostic Renalytix AI lands $29M

AI-powered kidney disease diagnostic Renalytix AI lands $29M | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
On Friday, New York-based startup Renalytix AI, maker of a clinical diagnostic that uses artificial intelligence to diagnose for kidney disease, landed $29 million in funding. This news coincides with Renalytix AI’s announcement that it will now be publicly traded on the London Stock Exchange.

Looking ahed, the company said the new money will be used to help it develop two products designed for early kidney disease detection and transplant management, including organ rejection. The first of its diagnostic tests, called KidneyIntelIX, is slated for a 2019 launch date. However, it still needs to go through FDA regulatory review.

KidneyIntellX was was born out of a partnership between the startup and the Icahn School of Medicine at Mount Sinai that was announced last May. As part of the deal Mount Sinai is also one of the shareholders in the company. The deal also let the company access Mount Sinai’s data warehouse, which has over three million patient records and 43,000 patient records in the BioMe BioBank repository.

Why it matters

The National Institutes of Health reports that more than 661,000 Americans have kidney failure and 193,000 have undergone a kidney transplant.

"Kidney disease is a major challenge for healthcare systems around the globe," Dr. Barbara Murphy, dean for Clinical Integration and Population Health at the Icahn School of Medicine at Mount Sinai, as well as a member a of the RenalytixAI's scientific advisory board, said in a statement. "We're responding to this critical unmet need by developing two products that will identify patients at risk for kidney disease progression and dialysis, and categorize the type of risk that will be experienced by kidney transplant patients.”
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How does Google want to apply artificial intelligence in healthcare?

How does Google want to apply artificial intelligence in healthcare? | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Recently, DeepMind's leaders announced its healthcare team will be combined into Google to help them become the "AI-powered assistant for nurses and doctors everywhere."

Observers say the move is part of a broader effort within Google to boost collaboration and communication among health projects.

In a statement, DeepMind leaders said the company has "made major advances in health care in AI research," including advances related to "detecting eye disease more quickly and accurately than experts; planning cancer radiotherapy treatment in seconds rather than hours; and working to detect patient deterioration from electronic records."

One of its most prominent projects is Streams, an app developed with the United Kingdom's National Health Service that clinicians can use to detect health issues, such as kidney failure. The app enables nurses and physicians to view patients' vital signs, test results and medical histories in one place.

In a statement, DeepMind leaders said its healthcare team will move to Google in an effort to expand Streams' reach. The leaders said they want Streams to become "an AI-powered assistant for nurses and doctors everywhere."

What are the prospects for Google’s AI initiatives in healthcare?

Artificial intelligence and machine learning have demonstrated their promise on a broad range of healthcare decision-making tasks, ranging from better readmissions predictions, financial forecasting and acute clinical diagnoses.

Alphabet's DeepMind group has pushed frontiers in AI at a dizzying pace, tackling everything from chess to automatically diagnosing eye disease. Therefore, its recent announcement that some of the more practically focused teams within DeepMind Health will move to Google and focus on commercializing AI capabilities has provoked strong reactions within the UK and the US.
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The Amazing Ways Artificial Intelligence Is Transforming Genomics and Gene Editing

The Amazing Ways Artificial Intelligence Is Transforming Genomics and Gene Editing | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

By 2021, consultant firm Frost & Sullivan expects that artificial intelligence (AI) systems will generate $6.7 billion in revenue from healthcare globally. One area that machine learning is significantly evolving is genomics—the study of the complete set of genes within an organism. While much attention has been paid to the implications for human health, genetic sequencing and analysis could also be ground-breaking for agriculture and animal husbandry. When researchers can sequence and analyze DNA, something that artificial intelligence systems make faster, cheaper and more accurate, they gain perspective on the particular genetic blueprint that orchestrates all activities of that organism. With this insight, they can make decisions about care, what an organism might be susceptible to in the future, what mutations might cause different diseases and how to prepare for the future.

Genome Sequencing and Gene Editing

Since the illnesses an individual experiences in a lifetime are largely determined by their genetics, there has been significant interest to better understand our genetic makeup for years. Our progress was stalled by the complexity and enormity of the data that needed to be evaluated. With advances in artificial intelligence and machine learning applications, researchers are better able to interpret and act on genomic data through genome sequencing and gene editing.

A genome sequence is a specific order of DNA building blocks (A, T, C, G) in a living organism; the human genome is made up of 20,000 genes and more than 3 billion base pairs of these genetic letters. Sequencing the genome is a critical first step to understanding it. The latest technology called high-throughput sequencing (HTS) allows the sequencing of DNA to occur in one day—a process that once took a decade when it was first done.

When changes are made to DNA at a cellular level, it’s called gene editing.

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Big things ahead for blockchain in healthcare, new report shows

Big things ahead for blockchain in healthcare, new report shows | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Blockchain is poised to go big in healthcare soon, according to a new study from CB Insights. The cryptographic digital ledger technology is highly secure and resilient, and while industries such as banking or retail are bullish on it, and already building on it in myriad ways, CBI finds that "still very early days for blockchain and healthcare applications."

Making inroads on blockchain now with smaller projects that do not involve patient data can help prepare healthcare organizations for larger blockchain tasks while adding value in the short time by cutting costs and streamlining data.

WHY IT MATTERS
Blockchain is emerging as what could soon be a must-have technology in the healthcare space, with numerous exciting potiential use cases – applications ranging from credentialing of practitioners to data sharing to supply chain management. Because of its robust privacy design and interoperability, it can apply to a wide range of healthcare needs.

In any application where "accessing complex data from different entities" occurs, CBI says blockchain is able to provide a consistent and standard chain of ownership and access to data. Properly implemented, it has potential for "tracking where a patient is, and what procedures/tests they’ve had" in a secure and scalable manner.

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By 2020, Bayer will take all of its digital media buying in-house

By 2020, Bayer will take all of its digital media buying in-house | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

German pharmaceutical company Bayer, maker of consumer health products such as Aleve and Advantix, is on a two-year mission to bring all media in-house. Bayer began building out its in-house programmatic operations in March 2017, and currently has a 10-person internal team that works in tandem with GroupM agency MediaCom on media buying. But starting in 2019, Bayer will drop this hybrid model and grow its internal marketing team to 20 or more people to handle everything from the strategy and planning of media buys to their execution.

“We realized that if we really wanted to be leading edge marketers, then we would need more expertise in the building, not only from a strategic level but a tactical level,” said Josh Palau, vp of digital strategy and platforms at Bayer.

Palau, who first spoke about this during presentation at the Programmatic I/O conference in New York in October, said the company is moving its media in-house to accomplish a variety of goals, including to increase the company’s own internal expertise around marketing, to drive better performance of its buys and decrease the cost of its buys and cut off agency fees. Palau would not say how much the company expects to save from the move, but that there will be cost-savings and more that the company can then put into marketing.

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Digital health tools: How the right IT solutions can deliver a better patient experience  #esante #hcsmeufr #digitalhealth

Digital health tools: How the right IT solutions can deliver a better patient experience  #esante #hcsmeufr #digitalhealth | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Healthcare organizations are responding to the consumerization trend by investing in IT solutions designed to improve the patient experience.

When these solutions are deployed the right way, they can help make clinicians' lives easier by improving the patient experience both before and after a care interaction.

 

On day one of the three-day Becker's Virtual Health IT Summit sponsored by Lenovo Health and Intel Nov. 6-8, two practicing physicians — Stephen Agboola, MD, scientific director for research and analytics at Partners HealthCare in Boston, and Larry Garber, MD, medical director for informatics and associate director of research at Reliant Medical Group in Worcester, Mass. — shared successes their organizations have had using connected health tools to improve the patient experience. Also on the webcast was Lenovo Health Global Healthcare Solutions Leader Bob Monteverdi, MD, who offered a vendor's perspective on using digital health to enhance patient experience.

 

How digital health tools are used: Active vs. passive engagement

The ways healthcare organizations use digital health to engage their patients fall into two buckets: active engagement and passive engagement. For the purposes of this article, active patient engagement refers to digital health tools that require users to interact with them in some way, such as entering in personal data or details. In contrast, passive patient engagement refers to digital health tools that don't require patients to take any additional steps, such as implanted sensors that automatically record select data points.

Dr. Agboola said he's seen success with an app he helped develop aimed at better managing cancer patients' pain. The app helps facilitate a survey that's distributed to the patient three times a week to proactively gauge and address their pain levels before they present at the clinic for routine appointments.

In this way, patients are actively engaging with the digital health tool, and Dr. Agboola noted that patients and clinicians reported feeling more connected to one another while using the app.


Via Florian Morandeau, Lionel Reichardt / le Pharmageek
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Florian Morandeau's curator insight, November 16, 1:38 AM

Digital health tools give clinicians access to more data to base their decisions off.

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Projet Cyborg : le CHU de Montpellier inaugure une extension de l’IRMB pour accueillir 8 start-ups dans le domaine des biothérapies

Projet Cyborg : le CHU de Montpellier inaugure une extension de l’IRMB pour accueillir 8 start-ups dans le domaine des biothérapies | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Le 7 novembre dernier, le CHU de Montpellier a inauguré l’extension de son institut de médecine régénérative et de biothérapies (IRMB) qui permet d’accueillir 8 start-ups impliquées dans le domaine de biotechnologies et des thérapies innovantes. Ce projet, soutenu par l’État et Montpellier Méditerranée Métropole dans le cadre du Pacte Métropolitain d’Innovation, fédère les acteurs de la recherche et de l’innovation en santé pour inventer la médecine de demain au bénéfice des patients du territoire.


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Google accusé de trahir des patients en prenant le contrôle d’une appli de santé  #esante #hcsmeufr

Google accusé de trahir des patients en prenant le contrôle d’une appli de santé  #esante #hcsmeufr | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Tout ça à cause de Streams, une application utilisée par les médecins anglais.

 

DeepMind, une société d’intelligence artificielle vient de transférer le contrôle de son application de santé, Streams, à Google. Une décision critiquée, car elle va à l’encontre d’une promesse de DeepMind, qui assurait que les informations personnelles de ses utilisateurs et utilisatrices ne seraient jamais liées à des comptes Google ou à leurs services.

À l'origine, l’application Stream était destinée à aider les médecins dans le suivi des malades atteints de lésions rénales aiguës et à prévoir leurs évolutions. Elle s’est ensuite développée pour servir d’assistant global pour tous les secteurs de la médecine.

 

 

Pour cela, la société avait noué en 2016 un partenariat avec le National Health Service, ou NHS, les services de santé publique du Royaume-Uni. Ce partenariat avait déclenché des suspicions sur la collecte de données et avait poussé le cofondateur de la société, Mustafa Suleyman, à assurer que les informations ne seraient «jamais liées, ni associées avec des comptes, produits, ou services Google».


Via Lionel Reichardt / le Pharmageek
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Des limites technologiques et réglementaires à l'usage des lunettes connectées en chirurgie

Des limites technologiques et réglementaires à l'usage des lunettes connectées en chirurgie | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
Le recours aux lunettes connectées lors d'opérations chirurgicales est actuellement expérimenté à l'hôpital Henri-Mondor (Créteil, AP-HP), mais fait face à plusieurs limites technologiques et réglementaires, a expliqué à TICsanté le Pr Romain Bosc, chirurgien plasticien et esthétique, auteur d'une revue de la littérature sur ces nouvelles pratiques en chirurgie maxillofaciale.

Le Pr Bosc exerce à l'hôpital Henri-Mondor et expérimente depuis quatre ans l'utilisation de lunettes connectées pour guider en temps réel les gestes du chirurgien, en phase pré-opératoire ou pendant une opération, grâce à la projection d'une image en réalité augmentée sur la zone à opérer, issue de données d'examens d'imagerie réalisés sur le patient.

Cette technologie est "régulièrement" utilisée pour "préparer une intervention chirurgicale", a-t-il souligné, citant le repérage pré-opératoire des vaisseaux lors d'une reconstruction du sein après un cancer, ou le placement de guides de coupe virtuels sur les os de la mandibule, dans le cadre de reconstructions après cancers de la tête et du cou.

Faire appel à la réalité augmentée n'est pas en soi une innovation pour la chirurgie, notamment dans des domaines où la plus grande précision est exigée, comme la neurochirurgie ou la chirurgie maxillofaciale lorsqu'il s'agit de poser des implants transoraux zygomatiques par exemple, a relevé le Pr Bosc.
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Optimizing Social Media Use in Health Care: The Mayo Clinic Social Media Network #esante #hcsmeufr #digitalhealth

Optimizing Social Media Use in Health Care: The Mayo Clinic Social Media Network #esante #hcsmeufr #digitalhealth | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

In this interview, EP Lab Digest talks with Farris K. Timimi, MD, Medical Director of the Mayo Clinic Social Media Network (MCSMN), and Lee Aase, Director of the MCSMN and Communications Director of Mayo Clinic’s Social and Digital Innovation (SDI) Team, about social media strategies in health care. 

 

Tell us about your medical background. How did you become involved with the Mayo Clinic Social Media Network (MCSMN)?

I am a cardiologist specializing in heart failure, and through that work have had an interest in patient involvement, such as with creation of our Patient and Family Advisory Committees. On major initiatives and in our basic structure, Mayo Clinic uses an physician/administrator model of shared leadership, with the administrator managing day-to-day operations and the physician leader helping to ensure medical relevance.

When the Mayo Clinic created what is now MCSMN, I was very interested in taking on the role of Medical Director.

 

What is the purpose of the MCSMN? When and why was it formed?

In 2011, Mayo Clinic created our Center for Social Media, which is now the Mayo Clinic Social Media Network, to help bring the social media revolution to health care. Our first goal was to ensure that Mayo Clinic staff and stakeholders had the guidelines, training, and resources to apply social media tools in support of clinical practice, education, and research. We also saw an opportunity to share globally what we were developing with colleagues, as well as learn alongside them as we navigated issues and concerns with these new technologies.

We see MCSMN as a catalyst to reduce the activation energy required to apply social media in health care organizations. By using our resources, colleagues can advance in their knowledge and capabilities more quickly than they would on their own.

Our association with Mayo Clinic also helps members gain internal buy-in; with these resources, they will be building on an approach and philosophy that has been shown to be safe and effective.

 

What is the role of social media in healthcare today? Additionally, what is the role of social media in healthcare education, research, and practice?

Social media has had a transformative impact on society as a whole, and health care is no exception. Through platforms such as Facebook, Twitter, YouTube, Instagram, and others, patients and caregivers can share their experiences as well as look for support and answers. They are able to overcome barriers of space and time to connect with others like them, even if they have a rare condition that is not shared by anyone in their immediate geographical area.

The patients were there first, but now medical professionals and organizations are seeing opportunities to listen, serve, and educate using these tools. 

 

Via Plus91, Lionel Reichardt / le Pharmageek
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Billions Will Be Poured Into AI Drug Development

Billions Will Be Poured Into AI Drug Development | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it

Although data flows in the drug development industry, the data center infrastructure used is unable to resume critical results. As an example, according to PAREXEL, a leading innovator of global biopharmaceutical services, the amount of data collected and used for regulatory submission for 400 trials is about 160 Terabytes. However, according to the company, with the influx of wearable devices in clinical trials, volumes such as 50 and even 80 Terabytes for a single study may be possible. As a result, this amount of data is not manageable on premise any longer.

In addition, pharma is a highly regulated industry and needs to comply with regulatory guidelines, while ensuring data privacy on patient identification rendering cloud exposure a difficult step. With GDPR in Europe – expanded to geo-location restrictions in certain countries – cloud technology has evolved into a compliant solution and more cost effective compared to on premise solutions.

Cloud based AI makes the difference

The main value of having a large quantity of high-quality data is the ability for computers to 'learn' from this data, the same way humans learn from experience. Modeling & simulation with development of 'in-silico patient' allow researchers to simulate the behavior of a drug and support identification of the most appropriate drug dosage. Machine learning –whether it is model based machine learning or deep learning – has the potential to train a model that will then be able to predict specific elements based on new input. This can be used to predict adverse events or to predict the possible risk of patient drop out and compliance to the treatment. Conversationalist bots, such as robot process assistant (RPA), are not simply reactive. They can now learn from behavior and therefore adapt to different contexts in a more flexible way.

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How AI and computer vision are reinventing wound care

How AI and computer vision are reinventing wound care | eHealth mHealth HealthTech innovations - Marketing Santé innovant | Scoop.it
One promising area in which artificial intelligence is rapidly advancing is computer vision, algorithms which process images. Healthcare entrepreneurs are in the midst of turning this technology toward healthcare, where algorithms can identify rashes and lesions, measure and analyze wounds, and bring colorimetric testing into the home — all using photos or short videos snapped by our smartphones.

“There’s a unique confluence here that is happening today that has allowed [these companies] to start to exist, which is the intersection of mobile, the prevalence of it, the power of those mobile devices being able to start to deliver on AI and computer vision at the bedside, and the advancements in frameworks especially in and around [AI],” Carlos Perez, founder and CEO of AI-powered wound care tech startup Swift Medical, said. “Think about where we’ve come from [2012], when the world was aghast that Google Brain could find a cat in a YouTube video. We’ve advanced to the point where we can deploy this technology at the bedside en masse and actually bring it to bare on a specific, meaningful application.”

MobiHealthNews dove into the world of AI for dermatology a few months ago — read on below for a look into the world of computer vision for wound care.

A black hole of data

Wound care is an attractive area for AI because the status quo leaves so much to be desired.

“Last year in the UK, the cost of chronic wound management was 5.4 billion pounds,” Yonatan Adiri, CEO of Healthy.io, said. “That’s about 5 percent of the British national healthcare spending. In England, because it’s the government and it’s a single-payer system, they actually measure every pound, every penny. The second piece was, instead of 5 billion pounds, 10 years ago it was 2.2 billion pounds, so this cost is exploding. And the third piece was the current way of measurements, and the current way of monitoring the wounds, is really inaccurate, non-repeatable and the result is that instead of having healing time [for] pressure wounds and skin ulcers of, let’s say six to 10 weeks max, at a certain price point, we’re seeing about 4,000 pounds per wound and 16 weeks because the nurses just can’t handle the throughput.”
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