Shaping the Responsible Adoption of AI in Healthcare
Tuesday, April 30, 2024, 11 A.M.
Bahen Centre for Information Technology, BA 3200
This lecture is open to the public. No registration is required, but space is limited.
Abstract:
As the use of artificial intelligence (AI) moves from being a curiosity to a necessity, it is clear that the benefit obtained from using AI models to prioritize care interventions is an interplay of the model’s performance, the capacity to intervene, and the benefit/harm profile of the intervention. We will begin the conversation reviewing the necessary data strategy to enable organization wide AI adoption and leading into a discussion of the core intuition behind foundation models. After a brief review of the kinds of use-cases that AI can serve across multiple medical specialties, we will discuss Stanford Healthcare’s efforts to shape the adoption of health AI tools to be useful, reliable, and fair so that they lead to cost-effective solutions that meet health care's needs. We will conclude with the rationale and vision for collaborative activities such as the Coalition for Health AI. The conversation will draw on examples from multiple specialities including Pathology, Cardiology, Internal Medicine, Surgery, Psychiatry and Oncology.
Bio:
Dr. Nigam Shah is Professor of Medicine at Stanford University, and Chief Data Scientist for Stanford Health Care. His research is focused on bringing AI into clinical use, safely, ethically and cost-effectively. Dr. Shah is an inventor on eight patents, has authored over 200 scientific publications, and has co-founded three companies. Dr. Shah was inducted into the American College of Medical Informatics (ACMI) in 2015 and 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.