Artificial Intelligence in Medicine: Opportunities and Challenges
Health care sits at the epicenter of recent advances in artificial intelligence (AI). In current years, research on AI applications in medicine has grown dramatically, reflecting both genuine opportunities for social benefit and persistent challenges in translating innovation into meaningful clinical impact.
AI has the potential to automate routine tasks, learn from large-scale patient data, advance precision medicine, and improve the efficiency and effectiveness of health care delivery. At the same time, enthusiasm for AI has contributed to inflated expectations and created an environment in which the quality, validity, and real-world relevance of research has been called into question.
This full-day conference brings together leaders in AI, medicine, ethics, law, and policy to examine where AI systems have delivered value, where they have fallen short, and what is required to responsibly realize their potential to improve the safety, quality, and equity of health care.
Keynote Speaker
John D. Halamka | President, Mayo Clinic Platform
, M.D., M.S., is president of the Mayo Clinic Platform, a digital initiative that brings together solution developers, data partners and healthcare service providers to transform healthcare. Today, Mayo Clinic Platform tools and solutions reach more than 54 million people globally.
Trained in emergency medicine and medical informatics, Dr. Halamka has been developing and implementing healthcare information strategy and policy for more than 40 years. Prior to his appointment at Mayo Clinic, he was chief information officer at Beth Israel Deaconess Medical Center, where he served governments, academia and industry throughout the world. As the International Healthcare Innovation Professor at Harvard Medical School, Dr. Halamka helped the George W. Bush administration, the Obama administration and governments worldwide plan their healthcare information strategies.
Dr. Halamka completed his undergraduate studies at Stanford University, earned his medical degree at the University of California, San Francisco, and pursued graduate work in bioengineering at the University of California, Berkeley. He completed his residency at Harbor — UCLA Medical Center in the Department of Emergency Medicine. He continues to practice emergency medicine and is Professor of Emergency Medicine and the Michael D. Brennan, M.D., President’s Strategic Initiative Professor at Mayo Clinic College of Medicine and Science.
Dr. Halamka has written 16 books and hundreds of articles. He was elected to the National Academy of Medicine in 2020 and serves on a number of boards, including the Coalition for Health AI, Vizient and the Milken Institute’s FasterCures Advisory Board. He and his wife run Unity Farm Sanctuary in Sherborn, Massachusetts, dedicated to the lifetime care of ill, disabled, senior, orphaned and surrendered farm animals.
Speakers
Kirsten Bibbins-Domingo | Editor in Chief, JAMA and the JAMA Network; Professor of Medicine, UC San Francisco
, PhD, MD, MAS is the 17th Editor in Chief of the Journal of the American Medical Association (JAMA) and the JAMA Network. She is the Lee Goldman, MD Endowed Professor of Medicine and Professor of Epidemiology and Biostatistics at the University of California, San Francisco. Dr. Bibbins-Domingo is a general internist, cardiovascular disease epidemiologist, and a national leader in prevention and interventions to address health disparities.
Hana El-Samad | Senior Vice President and Director, Institute of Computation, Altos Labs
Hana El-Samad is an internationally recognized scientist-engineer, systems thinker, and organizational builder pioneering the integration of AI, computation, and experimental biology. She is Senior Vice President and Director of the Institute of Computation at Altos Labs, where she built and leads an organization of scientists and engineers developing AI/ML capabilities for biological and therapeutic discovery. Her portfolio spans molecular AI, cell-state and multiscale modeling, AI-guided phenotyping, multimodal data integration, lab-in-the-loop approaches that connect computational predictions directly to experimental testing, as well as translational AI. Previously, as SVP and Director of SI3 (now, the Institute of Technology) and a Founding Principal Investigator at Altos, she created a multidisciplinary technology organization bringing together genomics, high-content imaging, proteomics, in vivo science, bioinformatics, histology, and data engineering—establishing the experimental and data foundation required for AI-enabled discovery at scale. Across these roles, she has set scientific and technology strategy, recruited senior leaders, built cross-functional organizations, and created operating models that translate ambitious research into durable capabilities relevant to aging, age-related disease, and drug discovery. Her industry leadership is grounded in a distinguished scientific career in academia advancing systems and control approaches to biology, synthetic biology, genomics, cell engineering, and de novo protein design. Prior to joining Altos Labs, Dr. El-Samad was the Kuo Family Endowed Professor and Vice Chair in the department of Biochemistry and Biophysics at the University of California, San Francisco. She is Editor-in-Chief of GEN Biotechnology, and her honors include a Packard Fellowship, the Paul G. Allen Distinguished Investigator Award, the Donald P. Eckman Award, the Byers Award in Basic Science, Cell’s “40 Under 40,” and election to AIMBE.
Kadija Ferryman | Faculty, Berman Institute of Bioethics; Assistant Professor, Johns Hopkins Bloomberg School of Public Health
is an anthropologist who studies race, ethics, and policy in health technology. Specifically, her research examines how clinical racial correction/norming, algorithmic risk scoring, and disease prediction in genomics, digital medical records, and artificial intelligence technologies affect racial health inequities. She is currently Faculty at the Johns Hopkins Berman Institute of Bioethics and Assistant Professor in the Department of Health Policy and Management at the Bloomberg School of Public Health at Johns Hopkins University.
Judy Wawira Gichoya | Professor of Radiology, Emory University
is the William and Kay Casarella Professor of Radiology at Emory university and leads the HITI (Healthcare AI Innovation and Translational Informatics) lab . Her work is centered around using data science to study health equity. Her group works in 4 areas - building diverse datasets for machine learning (for example the Emory Breast dataset); evaluating AI for bias and fairness; validating AI in the real world setting and training the next generation of data scientists (both clinical and technical students) through hive learning and village mentoring. She serves as the program director for radiology:AI trainee editorial board and the Emory University medical students machine learning elective. She has mentored over 60 students across the world (now successful faculty, post doc, PHD and industry employees) from several institutions around the world. She has received several awards including the most influential radiology researcher in 2022, and was a 2023 Emerging Scholar in the National Academy of Medicine.
S. Matthew Liao | Professor of Bioethics and Director, Center for Bioethics, New York University
Matthew Liao is Arthur Zitrin Chair of Bioethics, Director of the Center for Bioethics, Professor of Global Public Health, and Affiliated Professor in the Department of Philosophy at New York University. He is the author or editor of The Right to Be Loved (Oxford University Press); Ethics of Artificial Intelligence (Oxford University Press); Moral Brains: The Neuroscience of Morality (Oxford University Press); The Philosophical Foundations of Human Rights (Oxford University Press); Current Controversies in Bioethics (Routledge), and over 70 articles in philosophy and bioethics. He has given TED and TEDx talks in New York and CERN, Switzerland, and he has been featured in the New York Times, The Atlantic, The Guardian, the BBC, Harper’s Magazine, Sydney Morning Herald, Scientific American and other media outlets. He is the Editor-in-Chief for the Journal of Moral Philosophy, a peer-reviewed international journal of moral, political and legal philosophy.
Brad Malin | Professor of Biomedical Informatics and Vice Chair for Research, Vanderbilt University Medical Center
, Ph.D., is the Accenture Professor of Biomedical Informatics, Biostatistics, and Computer Science at Vanderbilt University, as well as Vice Chair for Research Affairs in the Department of Biomedical Informatics at Vanderbilt University Medical Center, where he co-directs ADVANCE AI Center. His research is in computational methods and infrastructure to enable broad data sharing and development of machine learned systems that are cognizant of their ethical, legal, and social implications (ELSI). He has led various grants from the NIH, NSF, PCORI, and ARPA-H, and he is currently leads the NIH’s flagship AI programs, AIM-AHEAD, where he leads the Optimization Core, and Bridge2AI, where he leads the Ethical and Trustworthy AI Core. He recently completed a five-year appointment on the Board of Scientific Counselors of the National Center for Health Statistics at the Centers for Disease Control and Prevention (CDC) and is currently part of the Speaker Program of the U.S. State Department. He also served as a consultant to the Office for Civil Rights at the U.S. Department of Health and Human Services, assisting in the development of guidance regarding de-identification in accordance with the HIPAA Privacy Rule. Among various honors, he is an elected fellow of the U.S. National Academy of Medicine (NAM), the American Academy for the Advancement of Science (AAAS), the American College of Medical Informatics (ACMI), the American Institute for Medical and Biological Engineering (AIMBE), Institute of Electrical and Electronics Engineers (IEEE), and the International Academy for Health Sciences Informatics (IAHSI). He was also a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) from the White House. He is an alumni of 91视频, holding a B.S. in biological sciences, an M.Phil. in Public Policy & Management, an M.S. in Machine Learning, and a Ph.D. in Computer Science.
Mark Sendak | Founder and CEO, Vega Health
, MD, MPP is the Founder and CEO of Vega Health, the trusted partner for health systems working to identify, integrate, and scale best-in-class AI solutions. Vega Health offers a proprietary platform installed in healthcare organizations’ local environments; a curated marketplace of validated AI solutions; and comprehensive implementation, evaluation, and monitoring services, all designed to ensure health systems realize real-world value from AI.
Mark previously served as Population Health & Data Science Lead at Duke Institute for HealthInnovation and co-founded the Health AI Partnership, a learning collaborative advancing operations and is a co-inventor of software to scale machine learning applications and real-world evidence generation across health systems. Mark and his team have published over 50manuscripts in top journals and has had work featured in The Wall Street Journal, MIT Technology Review, Wired, and STAT News. He has served as an advisor to national, including the American Medical Association, AARP, American Board of FamilyMedicine, White House Off ice of Science, Technology, and Policy.
Jenna Weins | Professor of Computer Science and Engineering, University of Michigan
Jenna Wiens is a Professor of Computer Science and Engineering (CSE), Associate Director of the Artificial Intelligence Lab, and Co-director of AI & Digital Health Innovation at the University of Michigan in Ann Arbor. Her primary research interests lie at the intersection of machine learning and healthcare. Wiens received her PhD from MIT in 2014, received an NSF CAREER award in 2016, was named to the MIT Tech Review’s list of Innovators Under 35 in 2017, was awarded a Sloan Research Fellowship in Computer Science in 2020, and most recently, received a Humboldt Research Award in recognition of her career achievements to date.
