AMIA 2023 Annual Symposium Plenary Sessions
Opening Keynote Presentation
Sunday, November 12, 2023
Precisely Practicing Medicine from 700 Trillion Points of Data
There is an urgent need to take what we have learned in our new data-driven era of medicine, and use it to create a new system of precision medicine, delivering the best, safest, cost-effective preventative or therapeutic intervention at the right time, for the right patients.  Dr. Butte's teams at the University of California build and apply tools that convert trillions of points of molecular, clinical, and epidemiological data -- measured by researchers and clinicians over the past decade and now commonly termed “big data” -- into diagnostics, therapeutics, and new insights into disease.  Dr. Butte, a computer scientist and pediatrician, will highlight his center’s recent work on integrating and learning from electronic health records data from over 9 million patients across the entire University of California, and how analytics on this “real world data” can lead to new evidence for drug efficacy, new savings from better medication choices, and new methods to teach intelligence – real and artificial – to more precisely practice medicine.
Atul Butte, MD, PhD is the Priscilla Chan and Mark Zuckerberg Distinguished Professor and inaugural Director of the Bakar Computational Health Sciences Institute at the University of California, San Francisco (UCSF). Dr. Butte is also the Chief Data Scientist for the entire University of California Health System, the eighth largest by revenue in the United States, with 20 health professional schools, 6 medical schools, 6 academic health centers, 10 hospitals, and over 1000 care delivery sites.
Dr. Butte has been continually funded by NIH for 25 years, is an inventor on 24 patents, and has authored over 300 publications, with research repeatedly featured in the New York Times, Wall Street Journal, and Wired Magazine. Dr. Butte has been elected into the American Association for the Advancement of Science (AAAS), American Institute for Medical and Biological Engineering (AIMBE), American College of Medical Informatics (ACMI), and National Academy of Medicine, and in 2013, he was recognized by the Obama Administration as a White House Champion of Change in Open Science for promoting science through publicly available data. Dr. Butte is also a co-founder of three investor-backed data-driven companies: Personalis (IPO, 2019), providing medical genome sequencing services, Carmenta (acquired by Progenity, 2015), discovering diagnostics for pregnancy complications, and NuMedii, finding new uses for drugs through open molecular data. Dr. Butte trained in Computer Science at Brown University, worked as a software engineer at Apple and Microsoft, received his MD at Brown University, trained in Pediatrics and Pediatric Endocrinology at Children's Hospital Boston, then received his PhD from Harvard Medical School and MIT.
Closing Keynote Presentation
Wednesday, November 15, 2023
Ziad Obermeyer is Associate Professor and Blue Cross of California Distinguished Professor at UC Berkeley, where he works at the intersection of machine learning and health. He is a Chan Zuckerberg Biohub Investigator, a Faculty Research Fellow at the National Bureau of Economic Research, and was named an Emerging Leader by the National Academy of Medicine. His papers appear in a wide range of journals (ICML, JAMA, Nature Medicine, the New England Journal of Medicine, the Quarterly Journal of Economics, Science), and win awards from professional societies in medicine and economics.
Dr. Obermeyer’s work on algorithmic bias is frequently cited in the public debate about artificial intelligence, and in federal and state regulatory guidance and investigations. He is a co-founder of Nightingale Open Science, a non-profit that makes massive new medical imaging datasets available for research, and Dandelion Health, a data platform for AI innovation. Previously, he was a consultant at McKinsey & Co., and an Assistant Professor at Harvard Medical School. He continues to practice emergency medicine in underserved communities.