Implementation and Evaluation of AI in Real-World Clinical Settings: Shaping the Responsible Adoption of AI in Healthcare

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. 

In-Person:

Mission Hall MH-1406
550 16th St
San Francisco, CA 94158

Or Zoom:
https://ucsf.zoom.us/j/91905714156?pwd=N3RsREtKdWlDcG1jUUtNK3BhYXlNQT09

Lecturer

Dr. Nigam H. Shah, MBBS, PhD
Professor of Medicine, and of Biomedical Data Science
Chief Data Scientist, Stanford Healthcare
Associate Dean for Research, School of Medicine
Associate Director, Stanford Center for Biomedical Informatics Research

About

Dr. Nigam Shah is Professor of Medicine at Stanford University, and Chief Data Scientist for Stanford Health Care. His research group analyzes multiple types of health data (EHR, Claims, Wearables, Weblogs, and Patient blogs), to answer clinical questions, generate insights, and build predictive models for the learning health system. At Stanford Healthcare, he leads artificial intelligence and data science efforts for advancing the scientific understanding of disease, improving the practice of clinical medicine and orchestrating the delivery of health care. Dr. Shah is an inventor on eight patents and patent applications, has authored over 200 scientific publications and has co-founded three companies. 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.