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Momentum doesn't begin to describe it... 🚀
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Morgan Cheatham
As the discourse shifts from models to compound AI systems / agents, we need better AI benchmarks to evaluate multi-modal and multi-step task performance, especially in healthcare and life sciences. When we wrote the first paper demonstrating ChatGPT's performance on the USMLE, we chose the US Medical Licensing Exam as a benchmark for accessibility, speed, and ease. This benchmark was never intended to represent AI model performance on real-world clinical tasks. Today, I still see so many research teams and startups using benchmarks (like the USMLE) that are ill-fitted for assessing the true clinical or scientific performance and utility of the models they are developing for real-world contexts. Benchmark development may be seen as a "less sexy" area of research, but it is of paramount importance. Years after the rise of the transformer, we still lack adequate benchmarks for so many single-step tasks in biomedicine. With compound AI systems (i.e., architectures that integrate multiple AI models to perform complex tasks) emerging, we need new benchmarks for agentic behaviors. I'd argue that developing an agent with novel capabilities without at least proposing a companion benchmark (if an industry standard does not yet exist) may hinder the adoption of said agent, especially for high-stakes workflows. Designing more benchmarks that capture/simulate real-world clinical and scientific workflows will help us mitigate the major discrepancies observed between in silico and in vivo performance and better support safe + effective deployment of AI in biomedicine. There are already brilliant people focused here, and we need more. DMs are open if you're researching or working in this area of multi-step/multi-modal benchmarking in healthcare and life sciences! #healthcare #ai #artificialintelligence #generativeai
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18 Comments -
Sandeep Pulim M.D.
Elon Musk’s xAI, Which Just Raised $6 Billion, Has Significant Potential To Disrupt Healthcare via Sai Balasubramanian, M.D., J.D. "The most obvious entry point for xAI is similar to what other large, technology companies are attempting to do: increase task automation, improve clinical workflows, and optimize clinician productivity. Technology giants are investing billions of dollars creating and training foundation models so that they can easily fit into the day-to-day healthcare workflow."
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Raghava Rao
Absolutely, great insights Rock Health. Focussing on what you're best at can be key. Optum and Walmart have struggled because they tried to do too much. Pure-play virtual health providers, like Amazon in retail, could excel by specializing and creating their own space. It's like playing to your strengths rather than spreading yourself too thin. Pure play may be the winners ultimately. Tele health is here to stay. Devicharan R. Neelam Sharma Balaji Prasad Goli
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Bobby Guelich
I caught up with Nikhil Krishnan of Out-Of-Pocket fame to get his take on the current state of the healthcare technology landscape. Up first: his current thoughts on what's exciting and where there are opportunities for AI-driven solutions. First half of our Q&A below 👇 — 🟩 Q: When it comes to AI, what area are you most excited about? Patient-facing solutions. The AI admin and back-office space has quickly become saturated, and incumbents will always have a distribution advantage here. Which is why I’m actually surprised there aren’t more players entering the patient-facing side. I think the traditional healthcare companies are too nervous to actually go into that patient-facing area. And it's also a regulatory gray area, so if you actually get traction, you can probably help shape how this stuff ultimately gets regulated. So right now, I think the greatest opportunities are for patient-facing AI tools. 🟩 Q: Where specifically do you see whitespace to develop patient-facing solutions? I think there’s still a lot of opportunity on the patient-facing automation side. A great example actually is automated lab results. There has been an issue for the last 3 years that lab results automatically get released to patients, and they see something's abnormal. The patient is trying to figure out what’s going on and what they've read. Part of this is explaining the result, which is something Elaborate is working on, and in some cases, actually, it's really useful for the patient to get that notice immediately with follow up steps, like scheduling a diagnostic. Another area is AI that can autonomously make workflow changes within a local system. Viz.ai is working on this automated workflow piece in the context of situations like stroke care coordination and hypertrophic cardiomyopathy. This requires not only automation in terms of being able to understand the context of multiple datasets, but also make the requisite workflow changes (e.g. escalating to the right specialist). These are particularly useful in time-sensitive areas. 🟩 Q: Any other AI whitespaces? Monitoring of AI models. It's one of the areas that's still unknown in terms of how do you give peace of mind to your buyer? It becomes really hard to actually evaluate and audit a lot of these AI algorithms without some form of data exhaust. I feel like one of the things that will happen is you'll see some form of certifying entity emerge that can give a gold standard to hospitals. 🟩 Q: What else are you thinking about as it pertains to AI? I do think that pricing is one of the more interesting components here. For example, in AI scribing, how you think about pricing changes a lot depending on if you’ve got a human in the loop or not. Because adding a human layer goes from near zero marginal cost to cost scaling linearly. One of the ways that companies will be able to differentiate themselves — especially from incumbents — is the pricing model.
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Kathryn Wetherby
Today, a little different post. I wanted to share a few personal thoughts on the start-up space and healthcare while highlighting my friend Divya Yerraguntla thoughts on emerging trends in healthcare investing. Healthcare has become a massive theme in venture capital and private equity. Health technology has created innovative solutions that revolutionize how we approach wellness disease management and healthcare delivery. Understanding the most prominent themes and health investing, from digital health to biotech breakthroughs, shows the trends shaping the future of private investment in healthcare. Digital health is reshaping traditional healthcare paradigms. From telemedicine platforms to wearable devices, start-ups are leveraging technology to enhance patient care, improve outcomes, and reduce costs. Investors are eyeing companies offering scalable solutions that streamline healthcare delivery, enhance accessibility, and empower individuals to take control of their health. Biotechnology is a hotbed of innovation, with breakthroughs in gene editing cell therapy and regenerative medicine promising to revolutionize treatment options for many diseases. Investors are allocating significant capital to buy tech startups with disruptive technologies and promising pipelines, recognizing the potential to address medical needs and generate substantial returns on investment. The era of one-size-fits-all medicine is giving to precision medicine, which tailors treatments to individual patients based on their genetic makeup, lifestyle, and environmental factors. With advances in genomics, molecular profiling, and biomarker identification, precision medicine promises to target therapies with greater efficacy and fewer side effects. Investors are betting on big startups pioneering precision medicine solutions, recognizing the value they bring to improving patient outcomes and reducing health costs. This week, my friends Divya Yerraguntla and Rashmi R. Rao from #HLWFAlliance are researching and covering emerging trends in healthcare investing. Add your thoughts to their posts, promoted in the comments below 👇 _________________________________________________________________________________ No more silos, just solutions! | Interdisciplinary outcomes uniting healthcare and wellness practices 🌟Follow our publication: https://lnkd.in/geruvmCj #HLWFAlliance #HLWFExpert #HLWF _____________________________________________________________________________
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Bobby Guelich
Here’s your recap of last week’s health IT news 🗞️ 👇 🤖 AI Products • Emergency Services, Inc. + Augmedix Go ED: The emergency medicine group adopted the new ED-specific AI ambient scribe solution. • Color + OpenAI: The cancer care tech company partnered with the GenAI giant to build a AI clinical decision support copilot. • AKASA Medical Coding: The AI RCM vendor known for its AI prior auth tool AKASA Authorization Advisor released a new GenAI medical coding solution. • Humata Health: The AI prior auth for providers vendor closed a $25M funding round led by healthcare org-backed funds The Blue Venture Fund and LRVHealth. • Wellsheet + Concord Hospital Health System: The AI-enabled Smart EHR UI solution announced a client-reported 16.3% reduction in length of stay and 40% decrease in time spent in the EHR via its partnership with Concord Health, as well as the release of its new LLM-generated handoff summary feature. 🍎 VBC • BSIM Healthcare Services + Innovaccer: The healthcare provider—embarking on its first VBC contract—adopted the pop health data platform for analytics. 🩼 Durable Medical Equipment • Parachute Health: The DME e-prescribing and ordering solution released an update that integrates prior authorization. ⚕️Clinical Staffing • Matchwell + Indiana Hospital Association: The clinical staffing service partnered with the hospital member org to create the first state-wide resource pool for temp staffing. 🧑💻 Virtual and At-Home Care • Deaconess Health System + KeyCare: The Indiana-based health system adopted the Epic-based virtual care provider for around-the-clock virtual urgent care. • UC Davis Health + Current Health: The health system launched a new RPM program for high blood pressure in partnership with Best Buy Health’s care-at-home platform. 🧠 Food for Thought: We came across a couple of good resources this past week on the current state of healthcare data information exchange: • This article in Health Affairs from Deven McGraw and Tina Grande provides a comprehensive overview of some of the patient health data abuses we've seen come to light in recent months, as well as a number of policy recommendations to improve the health information exchange landscape for all participants. https://lnkd.in/e_GEQ-JJ (h/t Alya Sulaiman) • This episode of Health Gorilla's InteropTalk gives a helpful update on the current state of affairs, with a particular focus on the state of trust across the health data exchange community and how the definition of "Treatment" may evolve. https://lnkd.in/e96AJG-5 (h/t Brendan Keeler) --- Reminder: you can sign up for the Elion Briefing to get the latest healthcare tech news delivered to your inbox each week 📬 👉 https://lnkd.in/e2UJ3ckP
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Jomo Kenneth Starke
Healthcare technology is in trouble. After the relative boom time we experienced through during the pandemic, the fervor to innovate in health systems and payers seems to have dried up. While organizations continue to post stellar earnings, they also continue to lay off experienced health technology people en masse. Why? I think it's time for a bit of honest reflection. 70% of all enterprise healthcare technology projects fail. 17% of of all large scale IT projects go so badly that they threaten the very existence of the company itself. Bridging Business & IT, LLC For projects with a total price tag of over $1MM, that failure rate jumps to over 90%. And the ever prescient Clayton Christensen believed that the failure rate for all new product introductions is 95%. This is not new information. What is new is the most recent E&Y Pulse Survey that has health system CIOs believing that 7 in 10 of their healthcare IT projects have had no discernible #ROI. None. And this is for the projects that didn't fail. https://lnkd.in/gRgVt_Xs This is an existential crisis that health technology must face honestly and soberly. Lack of planning and poor communication are the core culprits. Clunky and outdated Waterfall project methodologies can be blamed for many of these failures. And frankly Agile disciples could use a bit more planning before they start iterating so they know what they're building. There are, however, some problem actors and business models that need to be called out. The historically biggest culprits, in my humble opinion, are large, institutional, enterprise software vendors and their server-based architectures. For decades they feasted on seven figure licensing deals, sometimes humble-bragging to potential implementation partners about 5:1 or 7:1 implementation cost to license cost ratios. Companies just went along with it, because no one gets fired for buying IBM, right? But the failures in this segment are legendary. And many have indeed been a key cause in the parent company failure. As for the ROI, there was a bright spot in the E&Y Pulse Survey. Despite not having established a demonstrable ROI, 96% of them still wanted to move forward with the projects, believed the investment was worth it. So the issue isn't necessarily that the projects aren't generating value, the issue is that the organizations (and their vendors) didn't do a good job up front validating agreed upon ROI metrics and measures. They don’t fully understand the value it is (or isn't) creating. This is our collective job to be better at this. So what can we do to reduce the failure rate and get health systems and payers back into investing in #innovation? #ROI #startups #valueengineering #goldenpath #LCNC #opensource
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Louis Derick Payet
I always read Rock Health's digital health reports as they give a nice pulse feel for what is happening in the digital health funding space. Good to see funds raised in H1 2024 suggest funding in the sector seems to have stabilized at 2023 levels. Its no surprise the report emphasis the buzz around AI and healthcare. There have been clear winners in the AI healthcare space in the area of process and cost optimization and the R&D space. The impact of AI in care and treatment delivery is so far much more muted. One area I never though to look at AI was in its ability to bring together multiple healthcare pathways and digital point solutions into a more holistic seamless experience for the patient. There is a clear trend away from using stand alone digital health point solutions, and could AI address this challenge by facilitating the efficient integration of disparate processes and technology into unified care programs. I can see this happening with digital health products but this will be more tricky to do with physical care programs involving clinicians and HCPs. “AI is helping us combine multiple parts of the care journey, across all care experiences. In the future, benefits navigation, clinical guidance, and care delivery won’t be delivered by separate companies or point solutions within the healthcare ecosystem. They’ll be features that work in concert within products, and they’ll happen in under 90 seconds for a seamless patient experience.” – Glen Tullman, CEO, Transcarent and Managing Partner, 7wireVentures
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John H.
1. Physician Burnout is Increasing 2. Patient Satisfaction is Decreasing 3. Healthcare is Messed Up (Not just in PE backed rollups) Here's the Problem: Most of this is beyond our control. Why? There is So Much Unconnected Data That It's Impossible to Easily Pull it Together for Decision Support. But...there is Hope Coming. I recently met with a United excecutive and an innovative AI-based Decision Support Software Company that can address this move to Value Based Care. The Solution? 1. Technology....pulling All the Data together and making it Easy to Use for Primary Care Physicians 2. Time....This is going to take Energy and Elbow Grease 3. Patience....We have to stick with it and celebrate small wins. 4. TeamWork...... Between Payors, Providers, Technology, and Capital. What do YOU Think the Answer Is? Let's figure this out...Our health and economic strength depends on this. Comment/Follow and Call Me to Discuss https://lnkd.in/gUBAw7ZG
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Michelle O'Brien
Jeremy Knibbs and I caught up with Paul Wilder Bri Buch and Gurpreet (G.P.) Singh for a chat yesterday as we are watching the US interoperability journey with interest post the 21st Century Cures Act. We had the pleasure of Paul joining us at our Wild Health Cloud Summit in Sydney in 2022 for an armchair chat about what happens when you legislate to share health data using a stick and not a carrot. We were curious to see how things were tracking. CommonWell Health Alliance recently partnered with ELLKAY a nationwide leader in healthcare connectivity to support data exchange to 200 million patients across a network of 34 000 provider organisations in preparation for the next stage of their interoperability journey (TEFCA) the Trusted Exchange Framework and Common Agreement. The numbers seem mind boggling to us in Australia. Whilst Australia's population is a fraction of the US, we have not yet cracked the interoperability nut despite throwing billions $$ at the problem so we thought we would take a deeper dive on the US journey and our own as one of the themes at our WildHealth Summit in Melbourne on October 22nd. The program will be live next week and it’s one of our best yet! ( Watch this space!) As we can see from the Epic versus Particle dispute there is a lot we need to be across on our own journey to interoperability and a lot we can learn to avoid the same scars. #interoperability #datasharing #connectedcare
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Hamza Sellak, PhD
The defining factor isn't the size of the company or startup, but the vision behind it. Take OpenAI, for instance. Until last year, unless you were deeply embedded in the ML world as a computer scientist/researcher, or enthusiast, you might not have heard of OpenAI. Meanwhile, a giant like Google was dominating the scene. However, a few years back, OpenAI was just another small startup. Now, it's rapidly evolving into a major player in big tech. Why and how? It comes down to having a long-term vision, a clear roadmap, patience, and solid execution (i.e., talents). Even in the context of healthcare AI, where (small) startups face many challenges (including the ones mentioned), the principles of vision and strategy apply. While merging with big tech might seem like an option for some, if a startup truly believes in its vision and has a well-defined path to achieve it, it should forge ahead independently. The landscape is evolving, and like OpenAI, today’s small startups with clear, visionary goals could be tomorrow's industry leaders. #starup #founders #openai #google #healthcare
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Michelle Currie MS, RN, CPHQ, CPHIMS
👏 Previous research unveiled how #Teladoc Health leverages AI to proactively identify individuals at risk for uncontrolled diabetes outcomes over a year in advance. 👏 Teladoc's personalized health nudges significantly improved self-monitoring for type 2 diabetes, particularly for those identified as at risk for future complications. The nine-month study demonstrated a remarkable 3X increase in engagement. Additionally, there was a notable 0.4 reduction in A1c levels, with participants transitioning from 8.2% to 7.8% after receiving personalized health nudges through notifications on their mobile devices following AI risk identification. The impact soared when nudges were utilized to boost 1:1 coaching within digital programs designed for type 2 diabetes management. Teladoc has demonstrated that AI is beneficial in clinical care when applied thoughtfully and pragmatically. Find out more about these groundbreaking findings: [Link to the study](https://lnkd.in/gn2V9Ptn) 📊 #TeladocHealth #AI #DiabetesManagement #HealthTech #DigitalHealth #ResearchStudy
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Morgan Cheatham
One key reason why healthcare technologies like AI, telemedicine, and software haven't structurally lowered costs or broadened access for the entire system after decades of experimentation (excluding pure financial engineering of payer contracts) is the limited reimagining of care delivery itself, with asynchronous telemedicine as a notable exception. In the same way that digitizing physical paper failed to exploit the capabilities of a new computing medium for word processing, hosting physician-patient conversations over video does not transform the actual delivery of care. In telemedicine, many of the inputs (e.g., clinician time) and therefore cost structures of in-person care persist, which is why we often see fee-for-service telemedicine companies struggle to achieve economies of scale (i.e., growing revenues non-linearly while growing costs linearly). Until we deconstruct the components of a medical appointment – from intake and triage, to chart review, history gathering, physical examination, diagnosis, treatment, and follow-up – we will continue to be underwhelmed by the disconnect between the transformative potential of these technologies and real-world patient/system impact. I’m optimistic that the emergence of reliable and performant medical AI agents will urge us to perform this deconstruction and redesign the fundamental building blocks of a “medical appointment.”
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39 Comments -
Andre Heeg, MD, PhD
Big Tech is transforming healthcare, and the latest report from CB Insights breaks it down. Amazon, Google, Microsoft, and NVIDIA are not just dabbling in healthcare; they're revolutionizing it. Here is my take on some forensic profiling 😉 (based on the full report). 💡 Amazon is focusing on primary and specialized care, leveraging virtual platforms and partnerships to build a comprehensive healthcare ecosystem. Their goal? Making healthcare more accessible and efficient. 💡 Google is the data powerhouse, turning health data into gold for biotech innovations. With 90% of big tech activity in genetic therapeutics, Google is paving the way for groundbreaking advancements. 💡 Microsoft is the AI enabler, equipping healthcare organizations with cutting-edge tools to enhance clinical research, drug R&D, and care delivery. Their acquisition of Nuance Communications is a game-changer in integrating AI into healthcare. 💡 Nvidia stands at the forefront of smart hospitals and AI-driven drug discovery. Their powerful hardware and innovative AI solutions are set to redefine medical imaging and surgical applications. These tech giants are not just making waves—they're creating tsunamis in the healthcare industry. The future of healthcare is here, driven by relentless innovation and strategic investments. 👉 What are your thoughts on tech’s role in healthcare? 👉 How do you see these advancements impacting patient care and medical research? Let’s dive into this conversation! Share your insights and let’s explore the future of healthcare together. #HealthcareInnovation #TechInHealthcare #FutureOfMedicine
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Howard Forman
Newest episode of #HealthAndVeritas with guest, Mitesh Rao, MD, CEO of OMNY Health talking about democratizing access to healthcare data and improving health through more reliable information. Harlan Krumholz talks about "The business case for quality: estimating lives saved and harms avoided in a value-based purchasing model" an article in Health Affairs Scholar that returns us to the uncomfortable domain of asking why our "system" doesn't do more to save lives and improve health outcomes. I talk about Marijuana. I am concerned that we are watching a slow moving catastrophe due to the desire to decriminalize and reduce controls over Cannabis and THC-containing products (which is good) while paying too little attention to quality and regulations. Listen to the pod and tell me what YOU think. And please post your comments, tell a friend, and rate and review us on your favorite podcast app. Yale School of Management Yale School of Public Health Yale School of Medicine https://lnkd.in/ezj8qVqy
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Ben Reigle
AI in Healthcare is a hot topic. But what is the reality of it today vs a few years from now? This is what I wanted to dive into with our good friend Ankit Jain. This was a great conversation on AI and the Trough of Disillusionment. Trough of Disillusionment is a phase in the Gartner Hype Cycle that occurs when interest in a new technology wanes after initial hype and expectations are not met. Internet, cell phones, etc all went through this phase of failed ventures until the real use cases started to be come common place. It's hard to remember that the internet went through this. We had a wave in early 2000 and then it all broke when it wasn't being adopted as fast or just wasnt ready for real prime time. I think we are in this phase right now with AI being a hot topic and people can see the potential. Yet, full scale practical changing of my entire world or job isn't there yet (for most things). check it out... https://lnkd.in/gjg6w_m2
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10 Comments -
Roupen Odabashian MD, FRCPC, ABIM
This was a great episode with Amit Garg from Tau Ventures. Together, we discussed the current state of healthcare, startups, AI, and much more. I had so much fun, and learned a lot, and I am sure you will too. For the full episode, check out Delta: HealthTech Innovators. #AIinhealthcare #VC #tauventures
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Bobby Guelich
Here’s your recap of last week’s health IT news 🗞️ 👇 🥼AI Clinician Assistant • Suki : The AI scribe announced an SDK and APIs enabling developers to integrate ambient documentation into their applications. • Apricot: The gen AI pre-seed startup focused on reducing documentation overhead for home health nurses launched. • Tampa General Hospital + Palantir Technologies: The health system and the software platform are partnering to develop an AI care coordination and decision support platform. ☎️ AI Contact Center • Mediktor + Sensely: The AI symptom triage solution acquired the conversational member engagement platform. 📋 Patient Administration • Oracle (Cerner) + Loyal: The EHR now offers integration with the patient engagement solution through its Healthcare Marketplace. • HubSpot: The CRM and marketing platform announced it will now offer HIPAA support and sensitive data tools. 🏥 Provider and Practice Administration • LeanTaaS: The AI-enabled facility management solution released updates including: mobile-first live view of OR schedule, predictive staffing automation, and a gen AI solution allowing decision-makers to glean staffing and scheduling insights. ⚕️ Clinical Operations • Keragon: The HIPAA-compliant automation platform launched out of stealth with a $3M funding round. 🧑💻 Virtual and At-Home Care • AvaSure + CLEW: The virtual care platform is partnering with the AI-powered remote patient monitoring and analytics company to improve patient outcomes. 🍎 VBC • Evolent + Machinify, Inc.: The VBC org acquired AI Authorization assets from the AI operating system platform. • ProgenyHealth, LLC + Wildflower Health: The maternity and NICU case management solution is partnering with the women’s health VBC enabler to “help health plans fill gaps, collapse silos and integrate into existing clinical and operational workflows.” • Health Catalyst + Carevīve: The population health data and analytics company has completed acquisition of the cancer care management solution. 🧠 Food for Thought: • This article provided an interesting look at Nebraska Medicine’s efforts to design a next-generation hospital room, including the four technologies they’ve selected to anchor their work. https://lnkd.in/em-u-a5v • McKinsey released a survey of 200 global health system executives on their investment priorities. Among the notable findings, 88% listed AI as an area of high potential impact, yet only 40% have implemented any solution thus far and over 20% don’t have plans to invest in the next two years. https://lnkd.in/eK3CeqQ2
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Charlotte Kalafut
Great presentation by Dan Buckland, MD for those looking to design Health AI/ML models. "...if we have been poorly treating a demographic or population, that will show up in the clinical data. We might not have race, gender or zip code as an identifier in the original clinical data." shared Dr Buckland. Good insights to support the need of Asher Informatics PBC AI/ML independent equity performance audits, AI-Assess. Through a funded federal research contract, we've designed a tool in which we can provide independent real-world data subgroup population testing on clinical and signal AI/ML models and products. Right now, the MVP is designed to support #oncologyAI FDA 510K submissions and enable the FDA access to the testing of an algorithms performance and therefore better evaluate an AI/ML submission. We've partnered with Gradient Health to provide data that includes race, gender, age and we're utilizing Rhino Health's federated platform to be able to pull testing data from multiple sources. If you're an oncology AI developer, we're currently conducting feedback interviews and would love to connect.
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