These 20 people are not just theorizing about the whizzbang of hot technology but rolling up their sleeves and demonstrating its value in real-world settings—to improve diagnostic care, access information that can inform treatment, address health inequities, and ensure the financial sustainability of health provider systems that operate on razor-thin margins. Their collective work offers a blueprint for leveraging AI responsibly and (hopefully) ethically, from streamlining hospital operations and enhancing clinical decision-making to revolutionizing drug discovery.

The current AI evolution presents both opportunities and challenges. Health systems face increasing demands, including rising patient expectations and staffing shortages. Implementing AI and large language models (LLMs) can address these concerns by enabling faster and more accurate treatment plans, automating administrative burdens, and personalizing patient care. However, realizing AI’s full potential requires thoughtful application, ethical considerations, and a commitment to addressing disparities.

These 20 champion AI’s practical application, guiding health systems toward innovation without losing sight of humankind’s well-being. They exemplify how AI can enhance rather than replace human expertise—an essential message as we continue to adapt to this rapidly evolving landscape. By following their work, health-sector leaders and innovators can gain invaluable insights into deploying AI for meaningful impact.

Trailblazers Redefining Health Innovation

While many thinkers will wow you with the future possibilities of these technologies, the 20 on this roster demonstrate transformative influence on the future of diagnostics, operational efficiency, and personalized care while emphasizing responsible, ethical implementation. From academia to industry, they provide vital insights and direction into leveraging AI for better health outcomes. Their work underscores AI’s ability to augment human expertise, providing a roadmap for health systems to innovate without losing sight of patient-centric care. Thanks to them and the others appearing on our Medika Life 2023 and 2024 list, we define AI as “augmented implementation” and not artificial intelligence.

How were they selected? They are public-facing, sharing their thoughts in articles, books, keynotes, classroom talks, research papers, and conferences. They willingly share their knowledge with others on their social media platforms. They spark ideas and challenge our current thinking, and these behaviors make them invaluable to the future application of information and its human health impact. Each person appears in hyperlinks so that readers can explore the depth of their contributions and, whenever possible, follow them on their social media platforms.

20 Voices of Influence Shaping AI in Health

Regina Barzilay, PhD

Dr. Barzilay, an MIT professor and MacArthur Fellow, is revolutionizing oncology and drug discovery through AI. Her pioneering work in machine learning has led to breakthroughs in early cancer detection, particularly in breast cancer screening. As co-founder and AI faculty lead of the MIT Jameel Clinic and the AI Cures initiative, she’s spearheading efforts to deploy AI models for cancer risk prediction in hospitals around the globe and accelerate drug development for infectious diseases. Dr. Barzilay’s work in oncology and drug discovery is paving the way for screening policies and new treatments.

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Anthony Chang, MD, MBA, MPH, MS

Dr. Anthony Chang, a pediatric cardiologist and founder of AIMed, is a driving force in AI education for health professionals. His book Intelligence-Based Medicine has become a cornerstone text. Dr. Chang’s recent work focuses on developing AI-powered predictive models for pediatric cardiac care and implementing AI solutions to enhance hospital operational efficiency. His annual AIMed conference has become a global platform for sharing cutting-edge AI health innovation.

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Karen DeSalvo, MD, MPH

Google Chief Health Officer DeSalvo leads initiatives that leverage AI and big data to address critical public health challenges and promote health equity. Her work includes developing AI-driven tools for early disease detection in underserved communities and creating platforms that provide real-time health data analytics for policymakers. Dr. DeSalvo’s leadership in responsible AI use ensures that Google’s health technologies prioritize patient privacy and ethical considerations.

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Pamela Davis, MD, PhD

Dr. Davis is a distinguished researcher at Case Western Reserve School of Medicine specializing in AI-driven diagnostics and clinical applications. After 13 years as the Dean of the School of Medicine, she returned to the faculty. Her work centers on predictive algorithms for early disease detection and improved treatment planning. But Dr. Davis is an anomaly to this roster. She has no social media handles and her many published works are not curated carefully. Yet, tracking her contributions shows her depth and national influence on the future of AI in practice. With numerous published studies on AI’s transformative role in health, Dr. Davis continues to shape the future of diagnostic pathways.

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David Feinberg, MD, MBA

As Chair of Oracle Health, Feinberg champions using AI and cloud-based technologies to improve health outcomes. He focuses on predictive analytics and data-driven tools that enhance clinical decision-making and streamline hospital operations. His leadership drives innovation in health technology integration. Dr. Feinberg is widely recognized for his transformative leadership as CEO of Geisinger Health, where he pioneered initiatives in population health, precision medicine, and value-based care. His expertise in integrating technology with health-care delivery continues to drive innovation, making digital tools more accessible and impactful for providers and patients.

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John Halamka, MD, MS

John Halamka, President of the Mayo Clinic Platform, is a trailblazer in AI-driven health solutions, leveraging data and technology to transform patient care. Co-author of The Digital Reconstruction of Healthcare, Halamka is a leading voice on digital transformation, interoperability, and the ethical use of AI in medicine. His work at the Mayo Clinic focuses on developing scalable digital platforms and AI models to advance diagnostics, remote monitoring, and personalized medicine. With a background spanning emergency medicine, informatics, and policy, Halamka’s insights continue to guide health systems toward a more connected, efficient, and data-driven future.

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Taha Kass-Hout, MD, MS

Dr. Taha Kass-Hout, General Manager of Amazon Health AI, is a pioneer in leveraging artificial intelligence to drive advancements in healthcare delivery. With a background in clinical practice, public health, and digital innovation, he leads initiatives that harness AI for improved diagnostics, care management, and population health outcomes. Previously, as the first FDA Chief Health Informatics Officer, he championed data-driven approaches to public health. His leadership at Amazon drives scalable, data-driven health models that integrate machine learning with real-world applications, positioning him as a key influencer in the future of AI in health.

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Isaac Kohane, MD, PhD

Dr. Kohane, Chair of the Department of Biomedical Informatics at Harvard Medical School and co-author of The AI Revolution in Medicine: GPT-4 and Beyond, is a leading authority on the intersection of AI and clinical care. His research focuses on using machine learning for precision medicine and improving electronic health records. Dr. Kohane has been instrumental in developing AI models that enhance diagnostic accuracy and patient outcomes. His recent work explores the potential of LLMs, such as ChatGPT, in clinical decision-making and patient engagement.

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Daniel Kraft, MD

Dr. Daniel Kraft is the founder of Exponential Medicine and a visionary in personalized medicine approaches. He’s an inventor, a former F-16 flight surgeon, and always ready to champion others’ bold ideas. Dr. Kraft explores how AI can transform health delivery and disease prevention. Dr. Kraft’s recent initiatives focus on AI-powered tools for early diagnosis and patient engagement. His next chapter includes the very successful NextMed Health and the evolution of Exponential Medicine. NextMed Health 2025 will be held in San Diego on March 30 and April 2, 2025.

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Tom Lawry

Tom Lawry, soon to be the author of his highly anticipated new book Health Care Nation: The Future Is Calling, and It’s Better Than You Think, may redefine the intersection of technology and patient care. Already renowned as the author of Hacking Healthcare, Lawry has built a reputation as a leading AI strategist who advises organizations on integrating cutting-edge AI solutions to boost operational efficiency. His former role at Microsoft as Director for AI for Health and Life Sciences, Director of Worldwide Health, and Director of Organizational Performance for the company’s first health incubator cements his standing as a trailblazer in health innovation. He’s almost always a keynote favorite at conferences such as HLTH and HIMSS.

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Fei-Fei Li, PhD

Dr. Fei-Fei Li is a strong advocate for diversity and inclusion in AI, emphasizing ethical considerations and societal impact. She co-founded AI4ALL, a nonprofit dedicated to increasing diversity in artificial intelligence, and has played a pivotal role in shaping policies for responsible AI development. Her leadership continues to influence the global AI landscape, bridging technology with human values.

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Vivian Lee, MD, PhD, MBA

Dr. Lee, author of The Long Fix, is a pioneering health tech executive driving data-driven health transformation. Her recent work includes developing AI-powered platforms for value-based care models and implementing predictive analytics to reduce hospital readmissions. Dr. Lee’s initiatives as former president at Verily Life Sciences focused on leveraging AI to optimize care delivery across diverse populations.

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Peter Lee, PhD

As Corporate Vice President of Microsoft Health, Dr. Peter Lee spearheads initiatives that apply AI to solve complex health-sector challenges. His recent projects include developing AI models for precision medicine and creating cloud-based solutions for health data interoperability. In his role, Dr. Lee seeks to solve complex health-sector challenges by integrating cutting-edge technology with practical healthcare applications.

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John Nosta

John Nosta has earned his place as a top influence in the AI landscape—particularly in discussions surrounding ChatGPT and large language models—due to his visionary insights and ability to demystify complex technological innovations. His thought leadership bridges the gap between cutting-edge AI research and practical, real-world applications, making the transformative potential of these tools accessible to a broad audience. By articulating AI’s promise and ethical challenges, Nosta fosters a balanced dialogue that drives the industry forward. His forward-thinking perspective and engaging commentary not only illuminate the evolving impact of AI on various sectors but also inspire both startups and established companies to reimagine the future of technology. Nosta has an upcoming book that is expected to drop sometime in fall 2025.

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Ziad Obermeyer, MD

Ziad Obermeyer, MD, is the Blue Cross of California Distinguished Associate Professor of Health Policy and Management at the UC Berkeley School of Public Health, researching the intersection of machine learning, medicine and health policy. His work has exposed biases in clinical algorithms and highlighted disparities in care delivery. As a co-founder of Nightingale Open Science, he promotes data transparency and collaboration to advance medical AI. His contributions are reshaping predictive analytics and decision-making in healthcare. Before his full-time career in emergency medicine, he consulted pharmaceutical and global health clients at McKinsey & Co. in New Jersey, Geneva, and Tokyo.

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Neal Patel, MD, MPH

As the Chief Information Officer for Health IT at Vanderbilt University Medical Center (VUMC), Dr. Patel leads the integration of advanced technologies into health delivery. With more than two decades of experience in HIT, Patel has been instrumental in computerized physician order entry systems and electronic health records to enhance clinical and quality processes. He focuses on translating VUMC goals into informatics strategies, optimizing patient care, and improving safety and services across the care continuum. Dr. Patel’s work underscores the transformative potential of AI and LLMs in the provider system.

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Kyu Rhee, MD, MPP

As Senior Vice President at CVS Health, Rhee leads initiatives that leverage AI for health equity and personalized care. His recent projects include implementing AI-driven health risk assessments in underserved communities and developing machine learning models to predict medication adherence. Through his leadership, CVS has deployed AI-powered virtual care solutions expanding access to preventive services and helping to close care gaps while improving outcomes for diverse patient populations.

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Nigam Shah, MBBS, PhD

Dr. Shah, a professor at Stanford University, specializes in applying AI to clinical workflows and electronic health records. His recent work includes developing AI models for real-time clinical decision support and creating algorithms to identify patients for clinical trials. He has published extensively in peer-reviewed journals on machine learning applications in healthcare and co-authored chapters in Artificial Intelligence in Medicine. Shah also leads Stanford’s Center for Biomedical Informatics Research, advancing research on AI’s role in population health and precision medicine.

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Eric Topol, MD

Dr. Eric Topol is not just “a” trailblazer in digital medicine. He will likely be among those acknowledged singular voices bridging the possible with the practical. His groundbreaking work has consistently pushed the boundaries of health innovation. Dr. Topol redefined patient empowerment with his seminal book The Patient Will See You Now. He transformed the traditional healthcare model, advocating for a future where technology facilitates personalized, proactive care. As the author of Deep Medicine, he continues to champion the integration of AI in health, exploring its potential to revolutionize patient care. Dr. Topol’s visionary contributions and commitment to merging clinical expertise with cutting-edge technology have established him as a guiding voice at the intersection of care and innovation, making him a standout influencer in AI applications.

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Hal Wolf, III, FHIMSS

Harold (Hal) Wolf is the president and CEO of HIMSS, a global advisor and thought leader supporting the transformation of the health ecosystem through information and technology. If health-related smart technologies such as AI, ChatGPT, GenAI, and LLMs have a central home to discuss policies and implementation, it is HIMSS. Hal shepherds the world’s health information management community. While his staff advance science and policy, championing implementation throughout the ecosystem. Wolf and HIMSS are where theory meets action. Wolf is far more than a leader of a global society of import; he is the community’s ambassador to NGOs, governments, and industry.

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The Rise of Generative AI in Digital Health: Key Insights from Galen Growth

Beyond tracking the 20 listed in the year’s people to watch and the previous two years, following the Galen Growth executive briefing Generative AI in Digital Health – Hype or Reality? The report is a must-read for AI, ChatGPT, and LLM professionals. It reveals how nearly 4,000 digital health ventures leverage AI, with 2% focused on generative AI. Notably, 27% of these applications enhance health management, and over 330 AI-driven ventures have partnered with health systems in the past five years. This report offers critical insights into AI’s growing impact on digital health innovation.

Acknowledgments

I thank my Medika Life colleagues, including Drs. Robert Turner, Jeff Livingston, Hesham A. Hassaballa, Patricia Farrell, and Michael Hunter, whose commitment to public health information inspire. I am also grateful to the many sector professionals I engage at events such as CNS Summit, DHAI, HIMSS, HITLAB, HLTH, and ViVE—people who generously share perspectives and contribute invaluable recommendations. A shout-out to Christina Raish, our new associate editor at Medika Life, for her support in making this feature possible.

Special recognition goes to those who have appeared on past Medika Life lists and remain engaged in advancing health and well-being. Their commitment to meaningful change is commendable to individuals and the planet. These trailblazers continue to push boundaries, demonstrating an unwavering dedication to improving lives.

Since the dawn of civilization, humanity has been awed and challenged by technological progress—from the mastery of fire to artificial intelligence. Each era, from the Stone Age to the Iron Age and now the Information and Cognitive Age, has demanded careful consideration of how best to harness innovation. Today, as we navigate the era of “thinking” technologies, one truth remains unchanged: the power of human insight, courage, and empathy must guide progress.

—Gil Bashe, Editor-in-Chief, Medika.Life

Remember to Follow the Voices of Influence from our 2023 and 2024 Rosters:

Spot a broken link, typo, forgotten degree, or name misspelled?

Oops! Apologies! While care has been taken in compiling this list and adding social media links, things go wrong: a name is misspelled, a link is broken, or an incorrect social media handle is listed. Please do get in touch to address typos, amendments, or omissions by reaching gil.bashe@medika.life.

Thanks in advance and be healthy!

The post 20 People Who are Transforming the Health Ecosystem Through Practical Paths to Apply AI – 2025 Roster appeared first on Medika Life.

While we should welcome ready access to health data, viewing it without the interpretation of a seasoned clinical expert can fuel fear. This is especially true when worrisome data prompts you to reflexively rush off to “Dr. Google” – a source that knows neither empathy nor accuracy.

On behalf of myself, my family, and the patients whom I know, I’d urge those engaged in managing and improving health tech to recognize what now essentially amounts to a gap in care. You must integrate responsible, clear, and reassuring interpretative information into your apps and platforms. For patients, the reason for the health system’s very existence is much more than a “nice-to-have” feature; supplying it is an ethical imperative.

Patients should not be left to parse complex lab data alone, nor should they be making decisions based on fragmented information, especially when a single abnormal result might suggest a more serious situation than exists. While AI-generated engines process and summarize vast amounts of information in a blink, they lack the clinical judgment and humanity of a physician who knows a patient’s medical history. 

Further, AI-based models cannot currently account for every factor influencing personal health metrics, such as lifestyle, age, genetic predispositions, or recent health events. Even the language used by AI can inadvertently amplify fear; a model might describe results as “abnormal” or “high-risk” when the variation is clinically insignificant. And because AI still lacks a provider’s empathy and human touch, patients may rightly feel uneasy receiving sensitive information without the guidance of a health professional.

The Prostate Cancer Anxiety Trap: Low PSA and Free PSA

I recently underwent a routine prostate cancer screening, where the lab results appeared to signal a high risk. But without knowledgeable interpretation, the data I received was incomplete and could easily have been misleading. Consider my PSA (Prostate-Specific Antigen) tests: while a low PSA level, around 1 ng/mL, is well within the safety margin, a low percentage of Free PSA—such as 10%—could indicate a higher risk of prostate cancer, even when the PSA level itself does not suggest immediate concern. Interpreting these results on my own, the low Free PSA percentage triggered no small amount of anxiety about prostate cancer.

Conversely, a low PSA level combined with a low Free PSA percentage does not paint a clear picture; further medical consultation was required to interpret risk accurately. Age, overall health, and family history are crucial in clinical decision-making, but these factors are absent from raw diagnostic data. I was lucky to have the immediate benefit of my urologist’s expertise; without their judgment and insight, I might have jumped to conclusions, undergone unnecessary stress, or requested unneeded tests out of fear.

And it’s not just prostate exams. Thyroid function tests, heart-health markers, and diabetes screening metrics are three additional areas rife with potential confusion for patients reviewing their raw lab results. Elevated TSH readings, high LDL or CRP levels, or a single HbA1c result do not tell the whole story. These values are not necessarily predictive independently; they’re components of a broader clinical picture. Consumers need to be supported in reviewing that clinical picture, and AI needs to be part of providing that help.

Moving Toward Empowered, Informed Health Access

Despite the overall need to incorporate supports for interpreting health data, some health diagnostic platforms have begun to address consumers’ need to know by adding helpful explanatory notes to lab results or providing easy-access telehealth consults for patients seeking immediate explanations. A patient receiving an abnormal test result might be able to speak with a health professional or receive brief, plain-language insights about what the numbers indicate in general terms. These options can serve as bridges, guiding patients away from alarmist conclusions and toward actionable steps. At the very least, they provide patients with prompts for the questions to ask their health professional during a face-to-face meeting.

For those building and maintaining portal apps and platforms, acknowledging that many patients lack extensive health literacy and may be unfamiliar with basic medical terminology is crucial. Developers of health platforms should consider embedding visual aids, simplified summaries, or links to reputable health information sources to provide a foundation for stronger understanding before patients seek further information.

AI and Large Language Models: Help and Hazard

A recent JAMA study surprisingly suggests patients often prefer ChatGPT tools to physician conversations. While physicians understandably doubted the study’s conclusions, its data and the public conversation it sparked revealed that technology available in real-time to answer patients’ pressing clinical and emotional needs was sought and welcomed.

Large language models (LLMs) can provide general context, describing what test results typically mean and suggesting possible follow-up actions, like consulting a doctor if certain thresholds are exceeded. Technology can offer helpful insights, especially for people with conditions and concerns like cancer and other frightening health challenges requiring prompt access to professional input.  

LLM Cancer Mentor Apps such as Dave AI are revolutionary tools for cancer patients, caregivers, and physicians. It’s like having a WAZE for navigating the complex cancer diagnostic and care journey. Patients no longer have to wait for their next appointment to get answers to their questions.  Health tech innovators realize that diagnoses leave patients anxious between doctor visits, and the best solution may often be well-trained LLMs.  [See LLM Cancer Mentor “Dave AI” Offers WAZE-like 24/7 Personalized Support, Making it a Game-Changer in Patient Care.]

The Cost of Health Data Without Context

The rapid consumerization of health data has democratized healthcare in powerful ways, but its pace has opened gaps in care and introduced risks. The emotional toll can be high when consumers receive real-time results without contextual guidance. Data that might otherwise encourage patients to engage actively in their wellness may instead provoke anxiety, confusion, or even mistrust in their own body’s signals.

“In clinical trials and healthcare, acknowledging and addressing the psychological symptoms brought on by the diagnosis, prognosis, and treatment of many conditions is vital,” writes Emily Epstein, LMSW, a Weill Cornell staff members who advocate for the inclusion of mental health support research and medical settings. “When a provider overlooks the anxiety that accompanies the stress of managing physical symptoms, a disservice is done to the mental well-being of the patients and participants, which can have adverse effects on the trial itself,” she adds.

A Call for Physician-Guided Digital Health Experiences

Access to lab results is part of a significant and positive cultural shift in health, where the focus has moved toward patient empowerment and shared decision-making. However, for true empowerment, patients need more than raw data; they need empathetic guidance in understanding their data’s meaning in the context of their unique health profile. To address this, health systems and app developers should incorporate sophisticated LLM resources that help educate users about the strengths and limitations of raw lab data and how to navigate the journey better ahead.

Empowered patients are educated patients capable of better understanding their health journeys in partnership with their health providers. As we advance, let’s strive for a digital health environment where patients can access their results clearly and confidently and know that communication is always part of the care.

The post Promise and Peril of Instant Health Information Access for Consumers appeared first on Medika Life.

Technological advances, including AI, are like fire—destructive and essential. Our mastery of fire has been vital to industrial and technological progress, from smelting iron to the steam engine to sterilizing food and medical instruments.  But, unchecked, fire is a destructive, societal danger. Similarly, AI can be a force for positive change, but it requires a positive perspective and responsible use to avoid potential dangers and greater socio-economic disparities.

By tapping into AI’s potential, we can create a future where human ingenuity and machine learning work together to improve the well-being of people and the planet. For instance, AI can assist in medical diagnoses, climate change predictions, and disaster response, among other areas. But to make that possible, we will need the courage and curiosity to see AI as humanity’s partner rather than an unwelcomed competitor – to leverage its strengths to complement our own.

Language matters, so we might be better off and more equipped to apply smart technologies by thinking about AI not merely as “artificial intelligence but, at the same time, “augmented implementation.”  

AI is not theoretical. It’s already transforming drug research and discovery and patient care delivery. From the research bench to the patient bedside, augmented implementation accelerates the discovery of new drugs and optimizes clinical trials, assigning the right patients to the right protocol. In hospitals, AI enhances resource allocation, accelerates clinical decision-making, personalizes patient care, automates administrative tasks such as billing and scheduling follow-up appointments, and tracks supply-chain necessities to avoid drug shortages. These implementation advancements result in better patient outcomes, reduced health costs, and a more effective care delivery system.

So, what is the problem? It seems evident that embracing these information technologies can make us smarter and faster – even fail smarter and faster. We don’t even need to know coding.  Large language models (LLMs) with the proper prompts can generate code based on a natural language description of the desired functionality.  

Perhaps the problem isn’t the technology; it’s humanity.  While most believe that humanity will triumph over tech, people’s fears translate into “pump the breaks” reflexes. But go slow quickly also ensures guardrails are in place for its appropriate use.  These transformative informational technologies are happening; now it’s a question of protecting people’s privacy and well-being, using these platforms ethically and responsibly, and keeping our eye on the prize – people’s healthy lives and the planet’s sustainable future.

20 AI/ChatGPT/LLM Champions to Follow

Once again, selecting only 20 thoughtful pathfinders for this listing was a challenge. There are thousands of people writing, speaking, and commenting about AI. It remains a hot topic and is always trendy. This list is not an exclusive roster of people speaking about or explaining AI possibilities. Those that do appear are key voices of influence at the frontlines of AI, GenAI, ChatGPT and LLMs and are boldly guiding the health sector and other related industries to adapt to these technologies ethically and practically. There is no turning back! For that reason, it is important to follow their social posts, speeches, and writings. They are consultants, physicians, policymakers, teachers and theorists. What they say and write should inform opinions and directions. Follow them and get smarter faster or fail slowly.

On this list, you will notice several differences from our last roster. First, we begin with including an LLM model we have been tracking and recommend following closely. Dave AI was the topic of a previous Medika Life article and is a role model for those interested in the potential of LLM technology to augment the patient-care team’s abilities and desire to help and heal. Dave AI offers patients WAZE-AI-like information support.

We have also included an organizational policy leader to close the list—Hal Wolf, President and CEO of HIMSS. We have interviewed Hal before, and his global community, nearing 40,000 members, comprises health leaders and government representatives who are setting the parameters for how these smart technologies can be used wisely.

Acknowledgments

Special appreciation to Medika Life colleagues such as Drs. Robert Turner, Patricia Farrell, and Michael Hunter, who inspire and the many others from numerous circles I meet at meetings CNS Summit, DHAI, HIMSS, HITLAB, HLTH, and ViVE and who share their thoughts and contribute recommendations. Many who appeared on the initial list of global voices keep in touch and share news of sector colleagues who are in the thick of the conversation. Special acknowledgment to people who appeared on previous Medika Life lists and continue along the path to improve the well-being of people and the planet. These exemplary people are dedicated to improving people’s health and we applaud their efforts to make a difference.

Since the dawn of time, people have been in awe and fear about advances made in times marked by technologies—from fire to AI: the Stone Age, Iron Age, and now, today’s Information and Sustainability Age. Humanity must decide how best to deploy these transformative “thinking” technologies. The emphasis on objective and expansive (courageous) “thinking”—the human touch—remains constant.

Gil Bashe, Editor–in-Chief, Medika.Life

AI and ChatGPT Global Voices of Influence

Here is our Medika Life roster of 20 people to follow in alphabetical order—all-important voices to track and learn from in the coming years. We have included links to the social media platforms and bios wherever available.

Follow these Voices of Influence—they are accessible leaders who write and speak on the future of how AI, ChatGPT, GenAI, and LLMs will be essential to health system transformation and the future of care delivery.

Dave AI

Dave is the world’s first LLM conversational AI oncology mentor for cancer patients, bringing a new level of support for cancer patients and their families and trained on billions of unique data points and anonymized real-world patient journey information accumulated during eight years on the Belong Life platform. Learn how LLMs make a difference for patients and the care team, “Meet Dave” and see the practical possibilities and potential of LLMs.

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Anima Anandkumar, PhD

Anima Anandkumar is a Bren Professor at Caltech. Her work developing novel artificial intelligence algorithms enables and accelerates scientific applications of AI, including scientific simulations, weather forecasting, autonomous drone flights, and drug design. Anandkumar is a fellow of the ACM, IEEE, Schmidt Science, Guggenheim and Alfred. P. Sloan Foundations. 

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Brian Anderson, MD

Dr. Brian Anderson is the Chief Executive Officer and Co-Founder of the Coalition for Health AI (CHAI). He leads a national coalition developing technical standards and best practices for MLOps, including governance, testing, evaluation, and monitoring in Health AI Assurance Labs. Dr. Anderson led the Informatics and Network Medicine Division at Athenahealth, where he launched a new approach to clinical decision support leveraging machine learning models.

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Pascal Bornet

Pascal Bornet is an award-winning expert, author, keynote speaker, influencer, and thought leader in artificial intelligence. He has received multiple technology and artificial intelligence awards. Various research and consultancy firms rank him as one of the top 10 global experts in AI and Automation, and he was awarded Global Top Voice in Tech in 2019. He is the author of the best-seller and first reference book on Intelligent Automation.

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Lex Fridman, PhD

Lex Fridman, PhD, is a Russian-American computer scientist, podcaster, and artificial intelligence research scientist at the Massachusetts Institute of Technology on computer vision and autonomous vehicle systems, among other areas of specialty. Fridman also hosts the “Lex Fridman Podcast,” a popular podcast and YouTube series.

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Mo Gawdat, MBA

Mohammad “Mo” Gawdat is an Egyptian entrepreneur and writer. He is the former chief business officer for Google X and the author of the bestselling business books covering life and technology: Solve for Happy and Scary Smart – The Future of Artificial Intelligence and How You Can Save Our World. His premise is critical – “Humans design the algorithms that define the way that AI works, and the processed information reflects an imperfect world.”

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Aneesh Chopra, MPP

Aneesh Chopra is the Chief Strategy Officer of Arcadia, a health data platform that acquired CareJourney, the company he co-founded in 2014. Aneesh served as the first United States White House Chief Technology Officer during the Obama Administration and authored “Innovative State: How New Technologies Can Transform Government.‘ When it comes to policy and smart tech applications, he’s at the forefront of the conversation.

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Eric Horvitz, MD

Microsoft’s Chief Scientific Officer and an early AI champion for health and medicine going back many years, Dr. Eric Horvitz is among the founders and funders of Stanford’s 100-year longitudinal study of the impact of AI on Society. Dr. Horvitz is known for his contributions to AI theory and practice, with a focus on principles and applications of AI amidst the complexities of the open world.

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Andrej Karpathy, PhD

Andrej Karpathy was the senior director of AI at Tesla, where he led its computer vision team in the development of the Tesla Autopilot. He championed its neural network training, the science of “making it work, ” and deployment. His PhD focused on convolutional/recurrent neural networks and their applications in computer vision, natural language processing, and their intersection – his adviser was Fei-Fei Li at the Stanford Vision Lab, who also makes this list of 20 people to follow. He also did a stint at OpenAI.

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Tom Lawry

Tom Lawry is a leading AI transformation advisor to health and medical leaders globally, a top keynote speaker, and best-selling author of Hacking Healthcare – How AI and the Intelligent Health Revolution Will Reboot an Ailing System. Now the managing director of Second Century Tech, he is a former Microsoft leader who served as National Director for AI for Health and Life Sciences, Director of Worldwide Health, and Director of Organizational Performance for the company’s first health incubator. Prior to Microsoft, he was Senior Director at GE Healthcare, the founder of two venture-backed healthcare software companies, and a health-system executive.

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Fei-Fei Li, PhD

Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University and Co-Director of Stanford’s Human-Centered AI Institute. She was the Director of Stanford’s AI Lab from 2013 to 2018 and mentored others appearing on this Medika Life Top 20 list of AI voices to follow.

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Berci Mesko, MD, PhD

Bertalan Meskó, PhD, is known as “The Medical Futurist” and the Director of The Medical Futurist Institute. He analyzes how science fiction technologies can become a reality in medicine and healthcare. Dr. Mesko’s writings are must-reads—he provides incredible practical knowledge on how AI will transform the health sector. He holds a PhD in genomics and is an Amazon Top 100 author. His book, “The Future of Medicine,” outlines his journey as a medical futurist.

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Allie K. Miller

Allie K. Miller was the Global Head of Machine Learning Business Development for Startups and Venture Capital at Amazon (AWS), advising the world’s top machine learning researchers, founders, and investors. She was the youngest-ever woman to build an artificial intelligence product at IBM, spearheading product development across computer vision, conversation, data, and regulation for thousands of companies. Allie continues to explore how this technology will impact workflow.

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Andrew Ng, PhD

Dr. Andrew Ng is a globally recognized leader in AI. He is the Founder of DeepLearning.AI, the Founder and CEO of Landing AI, the General Partner at AI Fund, the Chairman and Co-Founder of Coursera, and an Adjunct Professor at Stanford University’s Computer Science Department.

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John Nosta

John Nosta is a cutting-edge thinker and speaker in the world of technology, science, medicine, and innovation. He is globally recognized among the foremost voices constantly pushing the envelope on how AI and ChatGPT will transform health settings and workflow. Nosta is a nonstop power thinker (and contrarian) and has more than 500 articles published on innovation topics. His writings on Psychology Today chronicle “The Cognitive Age.” John is someone who challenges the status quo. As a creative thinker; he’s also been the spark behind several multi-billion health products improving and saving lives.

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Tam C. Nguyen

Tam Nguyen holds multiple appointments, including Associate Professor at Melbourne Medical School and Deputy Director of Research at St. Vincent’s Hospital Melbourne. He has more than 20 years of experience in clinical trials, health and medical research, and research management, including tertiary teaching hospitals, medical research institutes, and universities across Australia. He is applying smart technologies to learn and engage faster. He is the co-editor of the recent book Artificial Intelligence in Medicine (Springer).

• LinkedIn

Ziad Obermeyer, MD

Ziad Obermeyer, MD, is the Blue Cross of California Distinguished Associate Professor of Health Policy and Management at the UC Berkeley School of Public Health, researching the intersection of machine learning, medicine and health policy. Before his full-time career in emergency medicine, he consulted pharmaceutical and global health clients at McKinsey & Co. in New Jersey, Geneva, and Tokyo.

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Brian Roemmele

Brian Roemmele is an author, scientist, researcher, analyst, connector, thinker, and doer. Brian became an early adopter of AI and neural networks and pioneered Prompt Engineering technologies and techniques to understand and extract information from AI platforms. He’s also a bit of a pop icon, and his works range from smart tech to how to apply Pokémon for customer acquisition.

• LinkedIn
• Medium
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Stela Solar

Stela Solar is the Inaugural Director of Australia’s National AI Centre, hosted by CSIRO. The Centre’s mission is to accelerate positive AI adoption and innovation that benefits businesses and the community. Currently, Stela also serves as Co-chair of the Commonwealth AI Consortium.

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Harold (Hal) Wolf III

Harold (Hal) Wolf is the president and CEO of HIMSS, a global advisor and thought leader supporting the transformation of the health ecosystem through information and technology. If health-related smart technologies such as AI, ChatGPT, GenAI, and LLMs have a central home to discuss policies and implementation, it is HIMSS. Hal shepherds the world’s health information expert community, and his staff advances the science and policy championing implementation throughout the health ecosystem. Wolf and HIMSS are where theory meets action.

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Spot a broken link, typo, forgotten degree, or name misspelled?

Oops! Apologies! While care has been taken in compiling this list and adding social media links, things go wrong: a name is misspelled, a link is broken, or an incorrect social media handle is listed. Please do get in touch to address typos, amendments, or omissions by reaching gil.bashe@medika.life.

Thanks in advance and be healthy!

The post As AI and LLMs Supercharge Digital Health Possibilities – Here Are Medika’s Top 20 ’24 Influential Voices to Follow appeared first on Medika Life.

The LLM Cancer Mentor App is a revolutionary tool for cancer patients, caregivers, and physicians. It’s like having a WAZE for navigating the complex cancer diagnostic and care journey.  No longer do patients have to wait for their next appointment to get answers to their questions. They now have a high-level concierge coach available 24/7, ushering in what innovation theorist John Nosta calls ‘The Age of Cognition ‘.

“Perhaps one of the most complex things about oncology is complexity itself. From clinical knowledge and understanding to articulating difficult concepts with patients. Part of what large language models (LLMs) offer is the ability to provide a cognitive assistant that serves up information that is organized and important, and delivers it away that is more relevant and understandable,” said Nosta to Medika Life. “This is perhaps most important with patients who often find the complexity of oncology to be one of the worst toxicities of both therapy and disease,” he added.

ChatGPT Controversial Perhaps, But Patient Preferred

Last year, a controversial JAMA study suggested patients often preferred ChatGPT tools to physician conversation.  A chatbot generated quality and empathetic responses to patient questions online in this cross-sectional study.  While physicians doubted the study’s design, it was evident from data and public conversation that technology available in real-time answering patients’ pressing clinical and emotional needs was sought and welcomed. Even Eric Topol, MD, a long-time AI advocate reports that augmented information can potentially save lives.

Now, the large language model (LLM) called Dave AI was created by Belong.Life increases patient engagement and provides personalized support.  Medika Life spoke with one of the world’s foremost digital health leaders, who marshaled the potential of technology and tapped medical and drug development experts and patient feedback systems to develop AI, ChatGPT, and LLMs tools to support cancer patient advocacy and innovation.  Eliran Malki, the co-founder and CEO of Belong.Life, is a proven entrepreneur and business leader who has founded, financed, and led several successful companies, including More IT Resources Ltd., acquired by Dell-EMC, Veracity Ltd., acquired by EMET, and others.  Together with Co-Founder Irad Deutsch, they launched Belong.Life almost a decade ago. Today, the company serves patients around the globe.

Malki’s blueprint for success isn’t a closely guarded secret – he consistently creates tech platforms that provide easily accessible, practical, and consistent value to users.  Belong.Life is a multilingual HIPAA, GDPR, and ISO-compliant community combining science, service, and solutions to unite patients, payors, product innovators, policymakers, and provers. It demonstrates that the LLMs can provide patients with the support essential to their cancer care journey – augmented information on-demand.

[The  Dave Cancer Mentor app can be downloaded here.]

Dave AI Created to Improve the Patient Journey

Eliran Malki, Co-Founder and CEO, Belong.Life: Dave AI was among the reasons we launched Belong Life – to improve people’s care journey and, ultimately, possibilities for outcome success. We trained this unique LLM (large language model) on an extensive knowledge base of 80 million discussions between patients and physicians. Over eight years, it’s accumulated knowledge of numerous physicians with 100,000 patients discussing the Belong Life app. The training process involved anonymizing and aggregating data to ensure patient privacy and security.

Gil Bashe, Editor-in-Chief, Medika Life: Incredible, eight years and 80 million discussions. How did you distill millions of exchanges and infuse them into Dave AI’s mind? Could you explain the process?

How Does the Dave AI LLM Work?

Malki: We started about six to seven years ago. There are a lot of questions that sometimes people lack the confidence to ask their physicians. People too often have only 10 or a maximum of 20 minutes with their provider. Patients want to ask the top two to three pressing questions, but you don’t do that if you are shy or intimidated to raise a topic.  At the same time, physicians want nothing more than help. Dave AI is a bridge between patients and their physicians – it helps prepare and strengthen the person-to-person relationship.

Here is a video summary of how Dave AI works:

With Dave AI, you can ask about treatment options, potential therapy side effects, clinical trials, or even managing your symptoms – pain, sexual function, or personal care. You’ll receive a supportive, comprehensive answer that covers all aspects of your query. We want to give the best services to patients at all hours, day and night, to educate and empower. Dave AI enables us to support millions of patients and prepare them to use their time with physicians productively. Everyone can get maximum support immediately. It’s suitable for payors, good for providers, and, most importantly, for patients.  It’s a model that combines the best of medicine, patient-physician relationships, and technology.

Dave AI Access for Everyone was Important to Belong.Life

Bashe: I have a question about cost. I understand there’s a free app download on any platform at no cost to the patient.

Malki: Yes, free of charge. We created three service levels to ensure this LLM technology is accessible to all.  The new Dave AI Mentor app is a free zone with premium services. The Dave AI Mentor answers questions and works with patients as a navigator along their cancer journey. It will ask about your upcoming tests; it will help people keep a diet and exercise regimen on track. Depending on your journey, it will be a health case manager and a constant ally. Dave AI will call you and answer questions that you ask, and it will also ask you questions to help model engagement. It’s similar to a coach,

We’re doing many things with hospitals, physicians and insurers that now cost $14.99 monthly. If you are an insurer, you can offer a patient, Dave AI, as a mentor or a case manager who’s available 24/7 and provides support with education and information for $150 per year. It’s the same for hospitals.

Bashe: So, are there different levels of Dave AI services to provide for people with varied economic and information needs?

Malki: Correct. There is a free version, a Pro version, and a Power Plus version. Everyone gets a seven-day trial to use everything. Most users renew. We start billing in January. If people don’t want to pay for an entire year midpoint in the cycle, they can use the free version first.  Many patients prefer the yearly subscription at $120 to $179, which offers unlimited access and added services.

Bashe: I’m curious – do you white-label Dave AI for hospital systems? For example, would it be possible for centers of excellence such as Memorial Sloan Kettering or Hackensack Meridian to secure a branded version of Dave AI catering to their patient needs?

Malki: Yes.  This is central to our service and patient care efforts. We are a technology company.  But we are, first and foremost, a patient-care service platform.  We want people to use and access the best of technology to improve their health.

Bashe: I wanted some background about basic free Dave AI. Now, some people are economically hard-pressed at the same time. Though $149 per year is not a lot when your life may be on the line, you have ensured that there is access to all, regardless of economics. How do Dave AI, Dave AI Pro, and Dave AI Pro Plus differ?

Imagine an Interactive Cancer Expert Available 24/7

Belong.Life’s new oncology AI mentor, Dave, provides accurate, personalized and accessible information instantaneously for people navigating the cancer journey. Dave is available on Belong’s Beating Cancer Together app.

Malki: Some people post 2,000 questions – some read  more than 5,000 posts.  Access to Dave AI for all is essential.  At the same time, someone speaking with an expert resource for 2,000 posts and chats should become a subscriber to the service because it is an incredible investment for us to create, operate, and continuously perfect the system.

Bashe: How many questions can you ask from the free Dave AI before going from Dave AI Pro to Dave AI Plus?

Malki: The free version is limited to 10 questions; the user must wait a week afterward—10 for the first week and then five per week. Many patients value the service, realize its immediate benefits, and are willing to pay. Taking a photo of a clinical document – uploading diagnostic test results – and understanding the document while you are still in the MRI waiting room is an incredible benefit, rather than waiting before you see the physician to discuss the written report. It is of considerable value that Dave AI can read, analyze, and provide feedback almost immediately.   

Scheduling a meeting with a physician is time-consuming and emotionally consuming. You call to wait days or weeks – a day feels like a lifetime.  Sometimes, you need questions answered immediately, seek elaboration, and say, “Please explain again; I didn’t understand that.” So, Dave AI is crucial for patients’ care and mental well-being.

Bashe: With Dave AI Pro Plus, people can ask as many questions as possible?

Malki: Yes.  As many as you want, all the time, 24/7.

How Does Smart Tech Get Smarter?

Bashe: I wanted to get a sense of the evolution of Dave AI. So, I understand that Dave AI is very smart today. How does Dave AI maintain that high level of intelligence week after week?

Malki:  Great question. This is a unique and critical accuracy feature that we patented.  It’s known as the Arch Methodology. The Arch stands for Accuracy, Responsibility, Compliance, and Hallucination-free. AI must always answer accurately; if Dave AI doesn’t know the answer, he can’t invent it. He will say, “I cannot answer.” Telling the AI what not to answer is as important as telling them what and how to respond.

We have several LLM multiplexers. [AS1] This is also one of our patents. All information goes through feedback classification, sentiment analysis, an RLHF Engine (Reinforcement Learning from Human Feedback), and a machine learning approach combining human guidance to train the AI tool..

Every change also goes through several tests and the automated ARCH-validated protocols.

Speed Accelerated for Clinical Trial Inclusion

We have been offering a clinical trial recruitment service for patients for the past six years. The average time for matching a patient to a clinical trial before  September 2023 was 5.4 days from when the patient started speaking to us.. Once we launched and added another LLM called Tara to our clinical trials matching program, the median connect time was 9 minutes, and the average was 2 ½ hours. The patient also can upload their documents, and the system will do all the work.

Eliminating the Tension of Waiting for Answers

The BelongAI Dave – Cancer Mentor app provides 24/7 accurate, personalized, and proactive support and information for people navigating the cancer journey.

Bashe: If you have 15,000 patients, those are 15,000 people who don’t have to wait 5.4 days.  There is also the issue of reducing anxiety levels for someone who has just been diagnosed with cancer. How do they take control of a situation when their life is out of control? They collect information and act on it. If they’re lingering in the trial search environment for five days or three days, that increases their anxiety levels. If they search for only three hours, that reduces their anxiety level.

It’s a little bit like having an interview for a job, and you’re waiting 5-6 days to find out if you got the job, or if they call you back in 3 hours and you got the job, what’s your anxiety level while waiting to hear about the job? It’s off the charts. By day 5 ½, you’re wondering why you didn’t get it.

Unintended cruelty is baked into the clinical trial enrollment and care system, which keeps people hanging. Dave AI and Tara AI eliminate that factor.

Malki: It gives them hope. The patient asked for and got information relevant to the clinical trial, whereas people generally wait till a physician tells them.

Bashe: The reality is that Dave AI hones the process. The patient isn’t necessarily going to run off and enlist in a trial; they’ll say to their doctor, “Look, I’ve gotten three possible trials from this database that fit my profile; what do you think?” It’s not an exclusion of the doctor; it’s accelerating the doctor’s ability to look over information and reply. Technology is not a replacement for a doctor; you understand that democratizing decision-making accelerates your enterprise’s decision-making pace. Same with the doctor.

The doctor, who’s cognitively sharp and psychologically sturdy, now has a patient who is much more engaged with the system. It’s not that Dave AI is the only trusted source; it’s that Dave AI is accelerating the patient’s ability to engage their doctor. The doctor can speak to the patient for five minutes and say, “I looked over your stuff; I think these are three good choices; I would go with this one as the priority, and tell me when you’ve enrolled.” The doctor never loses control over the patient. Oncologists want patients who remain alive.

I have a key question I will make sure to grab: How does Dave AI today get smarter tomorrow? What’s the rate of ability to make Dave smarter?

Malki: There are several factors involved in being smart in AI.. If you want chats, you will need Open AI, Gemini , or something like that, as you see in a mixed style, or Falcon, which is among the best. There are top five in the world as generative AI, and we’re just using three of them, running them on our classifications and our data – there’s no one in the market with our data. No one has the same physician-patient discussion database.

What makes us much better is that we added data from Dave AI’s patient exchanges. We deploy these patient discussions, remarks, and feedback. Dave AI is continuously improving.

Layers and Levels to Ensure Accuracy

Malki: 

We took the platform of AIand built three levels of what we call autonomous AI. Level 1 is controlled;. This is the easiest step forward for pharma, the FDA, and regulations. Gen 2 – this information is 100% accurate because the first one is pre-defined and pre-scripted; I have the approved answers, and the physician sends the second one.

Level 2 is a generative AI agent for specific documents, only . That’s amazing for hospitals, especially for logistical or administrative questions. Information that can lower stress and free the professional team.

Level 3 is a fully automated conversation with AI.  This is a Highly scaleable and valuable solutions

Bashe:  We’ve entered the cognitive age. With large language models, you’re in conversation. It understands that there’s a conversational tone to every exchange. You can use the LLM for half an hour or 40 minutes until you feel you’ve exhausted your train of thought.

Malki: Every payor, every provider, and every patient needs access to these platforms  as triage services to lower stress – the burnout level for professionals and increase the value to patients.  To review for Medika readers, here are the three Dave AI service options:

Dave Pro:

• Proactive check-ins with users about previously discussed concerns, scheduled treatments, and more.
• Precise, comprehensive, and empathetic answers to cancer-related questions and challenges.
• Document analysis and explanations of clinical terminology in easy-to-understand language.
• Access a personalized, continuously updated library of information on treatment options, side effects, and emotional well-being.
• Medication management, appointment notifications, and reminders.

Dave Pro Plus offers Dave Pro features through Tara, Belong.Life AI-powered assistant that matches patients to clinical trials based on their unique medical situations and locations. Through ongoing searches, Tara identifies new treatments and clinical trials and shares easy-to-read monthly summaries to update patients on treatment possibilities.

Dave Community allows patients to interact with Dave in a public forum, enabling users to understand other patients’ challenges and interactions with Dave.  

So, what do doctors think about Dave AI?  

We spoke with Ilya Iofin, MD, the Chief of Orthopaedic Oncology Service at Mount Sinai Hospital.

“Thank you, Gil. I first started working with Belong in 2017 or 2018.  Dave AI gives accessibility because you have this additional resource where anyone can understand the answer. AI is trained and based on what physicians say. You can use medical lingo and confuse everybody or try to explain it in terms that a reasonably intelligent person can understand. I think AI will do the same thing if AI learns from physicians who can get their thoughts and information across in reasonable human speech.

“Specialized medicine, especially oncology, differs from any other field. I’m a physician. If I talk to a car mechanic, he needs to explain, in terms I understand, how a car and engine work. Or I’ll just be as confused as the guy who knows nothing about cars. That’s the benefit of this LLM for people confronting cancer.”

Welcome to the Age of Cognition

Dave AI and LLM enable patients to navigate the complexity of medical care – from diagnosis to treatment to being in dialogue with their care team – which are critical to outcomes.  Malki and his team of engineers, physicians, medical professionals, and patient allies are showing us that LLM is not space-age technology.  LLM enables people diagnosed with cancer to overcome one of the disease’s biggest challenges: learning a language they never thought or wanted to understand.

Patient Advisory

Medika Life has provided this material for your information. We note that this platform and information provided are not intended to substitute for the medical expertise and advice of your health care provider(s). We encourage readers to discuss any clinical decisions on treatment or care with a health care provider. The mention of any product, service, or therapy is not an endorsement by Medika Life.

The post LLM Cancer Mentor “Dave AI” Offers WAZE-like 24/7 Personalized Support, Making it a Game-Changer in Patient Care appeared first on Medika Life.