AI for Care Delivery – Collin Stultz

This episode is in collaboration with MIT Sloan Healthcare and BioInnovations Conference, an event that brings the healthcare ecosystem together. On today’s episode, Naji hosted Dr. Collin Stultz, a distinguished professor at MIT and Harvard, and a practicing cardiologist. Collin shared his inspiring journey from his roots in Jamaica to his groundbreaking work in AI for healthcare. Collin emphasizes the potential of AI to enhance patient care by analyzing vast amounts of data, which can uncover crucial insights that healthcare providers might miss. He also highlights the development of digital twins for personalized medicine, allowing simulations of drug effects on patients. Additionally, they delve into the importance of addressing biases in medical data to ensure equitable healthcare for all. Collin's insights offer a glimpse into the future of medicine, where technology and data play pivotal roles in improving patient outcomes.

"Failure Makes You Better"

MEET OUR GUEST Collin Stultz Professor in Medical Engineering and Science, Professor of Electrical Engineering and Computer Science, Co-Director of the Harvard-MIT Program in Health Sciences and Technology, member of the Research Laboratory of Electronics, and associate member of the Computer Science and Artificial Intelligence Laboratory.

Collin Stultz is Professor in Medical Engineering and Science, Professor of Electrical Engineering and Computer Science, Co-Director of the Harvard-MIT Program in Health Sciences and Technology, member of the Research Laboratory of Electronics, and associate member of the Computer Science and Artificial Intelligence Laboratory. Collin is also a practicing cardiologist at the Massachusetts General Hospital (MGH).

Collin’s scientific contributions have spanned multiple fields including computational chemistry, biophysics, and machine learning for cardiovascular risk stratification. He is a member of the American Society for Biochemistry and Molecular Biology and the Federation of American Societies for Experimental Biology and he is a past recipient of a National Science Foundation CAREER Award and a Burroughs Wellcome Fund Career Award in the Biomedical Sciences.

Currently, research in his group is focused on the development of machine learning tools that can guide clinical decision making.