In this edition of Existential Medicine, we take a look at the world of AI and machine learning-powered medicine at the research, clinical and ethical levels. This event will focus on the historical intersection of mathematics, technology and patient care, and the future state of AI within medical practice. Topics will include predictive and precision medicine, data privacy and bias, and how these new tools will shape the future of the lab and hospital floor alike.
Moderator:
Katie Link is an AI Resident at X, the moonshot factory (formerly Google[x]). She has a background in neuroscience and computer science from the Johns Hopkins University and collaborates on research at the Allen Institute for Brain Science and the Mount Sinai AI Consortium (AISINAI), where her work focuses on machine learning applied to biomedical problems.
With special guests:
Dr. Berk Kapicioglu is head of machine learning at OccamzRazor, where he develops computational tools to identify drug targets for Parkinson’s disease. Prior to that, he was head of machine learning at Foursquare Labs, and a research scientist at Sense Networks. He received his PhD from the computer science department at Princeton University, and his BA from the computer science, mathematics, and philosophy departments at the University of Pennsylvania. His work has been published at venues such as AISTATS, UAI, IJCAI, RecSys, and NeurIPS.
Eric Karl Oermann, M.D. is an Instructor of Neurological Surgery in the Mount Sinai Health System and the Director of AISINAI, Mount Sinai’s artificial intelligence research group. He studied mathematics at Georgetown University with a focus on differential geometry and completed a postdoctoral fellowship at Google (Google Health / Verily Life Sciences). He is interested in weakly supervised learning, reinforcement learning with imperfect information, and in building artificial neural networks that more accurately model biological neural networks (“machines that think like humans”). As a physician, he is also interested in the application of deep learning to solve a wide range of practical problems in the medical sciences for improving clinical care.
Suchi Saria, PhD is an internationally renowned leader in AI and health. Most recently she was named to World Economic Forum’s Young Global Leaders, Popular Science’s “Brilliant 10”, Technology Review’s “35 Innovators under 35” and National Academy of Medicine’s Emerging Leaders in Health and Medicine. She holds a John C. Malone endowed chair at Johns Hopkins where she leads the one of the top labs nationally in AI and Health. She is also part of several efforts by the National Academies on learning and health. She is also the founder and CEO of a stealth mode company that’s working towards empowering providers with real-time access to inferences that make care safer and more efficient.