Building Fair, Useful Reliable Models at Stanford Healthcare

February 14th, 2023

We will discuss technical as well as practical considerations in ensuring that the adoption of AI in healthcare is fair, useful, reliable and has enterprise value. We will begin with an overview of existing recommendations for responsible AI, identify the gaps in existing recommendations and discuss our approaches for bridging those gaps.

Nigam Shah

Dr. Nigam Shah is a Professor of Medicine (Biomedical Informatics) at Stanford University, Associate CIO for Data Science at Stanford Healthcare, and a member of the Biomedical Informatics Graduate Program as well as the Clinical Informatics Fellowship. Dr. Shah is also the inaugural Chief Data Scientist for Stanford Health Care. His research focuses on combining machine learning and prior knowledge in medical ontologies to enable use cases of the learning health system. Dr. Shah received the AMIA New Investigator Award for 2013 and the Stanford Biosciences Faculty Teaching Award for outstanding teaching in his graduate class on “Data driven medicine”. Dr. Shah was elected into the American College of Medical Informatics (ACMI) in 2015 and was 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.