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Dr. Baker is Bing Professor of Human Biology and Professor in the Health Policy group at Stanford University. He is a health economist who applies economic and statistical analysis to study challenges facing the healthcare system. Professor Baker teaches undergraduate and graduate courses at Stanford, and has published widely on a range of healthcare system and financing issues. Professor Baker also holds appointments as Professor of Economics (by courtesy) at Stanford, Senior Fellow of the Stanford Institute for Economic Policy Research, and Research Associate of the National Bureau of Economic Research in Cambridge, MA. He is a former Chair of the Department of Health Research and Policy at Stanford.
Dr. Hernandez-Boussard is Associate Professor at Stanford University in Medicine (Biomedical Informatics), Biomedical Data Sciences, Surgery and Epidemiology & Population Health (by courtesy). Her current work utilizes high-volume digital data to monitor, measure, and predict healthcare outcomes using natural language processing and machine/deep learning techniques to analyze both structured and unstructured data. Through this infrastructure, her team captures heterogenous data sources, transforms these diverse data to knowledge, and uses this knowledge to improve patient care and outcomes.
Dr. Lungren is Co-director of the Stanford Center for Artificial Intelligence in Medicine and Imaging, and Medical School Faculty in the Department of Radiology at Stanford University Medical Center. Dr. Lungren’s NIH- and NSF-funded research is in the field of AI and deep learning in medical imaging, precision medicine, and predictive health outcomes. His work has been featured in national news outlets such as NPR, Vice News, Scientific American, and he regularly speaks at national and international scientific meetings on the topic of AI in healthcare.
Dr. Shah is Associate Professor of Medicine (Biomedical Informatics) at Stanford University, and serves as the Associate CIO for Data Science for Stanford Health Care. Dr. Shah's research focuses on combining machine learning and prior knowledge in medical ontologies to enable the learning health system. Dr. Shah was elected into the American College of Medical Informatics (ACMI) in 2015 and inducted into the American Society for Clinical Investigation (ASCI) in 2016. He holds an MBBS from Baroda Medical College, India, a PhD from Penn State University and completed postdoctoral training at Stanford University.
Dr. Yeung is Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. She is affiliated with Stanford’s Clinical Excellence Research Center, and serves as Associate Director of Data Science for the Center for Artificial Intelligence in Medicine & Imaging. Dr. Yeung’s research focuses on computer vision, machine learning, and deep learning for interpreting diverse types of visual data. She has also served on the National Institute of Health's Advisory Committee to the Director Working Group on Artificial Intelligence.