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Artificial Intelligence and Health Care

When: Thursday, April 30, 2020 | 2:00 to 4:00 pm ET

This free webinar, jointly hosted by the National Academy of Medicine (NAM) and the U.S. Government Accountability Office (GAO) will explore the vision, opportunities, challenges, and implications of the use of artificial intelligence (AI) in health care. Speakers will review two recent publications focused on AI and health care published by the NAM and GAO. Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril was published in December 2019 and outlines current and near-term AI solutions; highlights the challenges, limitations, and best practices for AI development, adoption, and maintenance; offers an overview of the legal and regulatory landscape for AI tools designed for health care application; and outlines key considerations for moving forward, including prioritizing the need for equity, inclusion, and a human rights lens for this work. GAO’s technology assessment Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development discusses current and emerging AI technologies available for drug development and their potential benefits; challenges to the development and adoption of these technologies; and policy options to address challenges to the use of machine learning in drug development. Machine learning has the potential to increase the efficiency and effectiveness of the drug development process, decreasing the time and cost required to bring new drugs to market, but several challenges hinder its adoption and impact. The report identifies policy options to address these challenges centered around promoting basic research, increasing data access and sharing, establishing standards, developing human capital, clarifying regulatory certainty, and maintaining the status quo. 

This webinar will provide an overview of each publication and feature a panel discussion of experts after each overview. 

As a courtesy to the individuals from Stanford University involved in this webinar the Stanford Center for Continuing Medical Education is pleased to offer CME credit for this activity. To access the CME information and to claim credit please visit: https://stanford.cloud-cme.com/AIHealthcare


Agenda

2:00pm | Welcome

  • Michael McGinnis, National Academy of Medicine
  • Tim Persons, U. S. Government Accountability Office

2:10pm | Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril: An NAM Special Publication

  • Michael Matheny, Vanderbilt University Medical Center and the Department of Veterans Affairs
  • Sonoo Thadaney Israni, Stanford University

2:25pm | Panel Discussion

  • Jack Resneck, American Medical Association
  • Marelize Gorgens, World Bank
  • Gil Alterovitz, U.S. Department of Veterans Affairs
  • Glenn Cohen, Harvard Law School

2:50pm | GAO Technology Assessment: Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development

  • Karen Howard, U.S. Government Accountability Office
  • Rebecca Parkhurst, U.S. Government Accountability Office

3:05pm | Panel Discussion

  • Ken Getz, Tufts Center for the Study of Drug Development
  • M. Khair ElZarrad, FDA Center for Drug Evaluation and Research
  • Danielle Friend, Biotechnology Innovation Organization

3:30pm | Q&A

4:00pm | Adjourn


As a courtesy to the individuals from Stanford University involved in this webinar the Stanford Center for Continuing Medical Education is pleased to offer CME credit for this activity. To access the CME information and to claim credit please visit: https://stanford.cloud-cme.com/AIHealthcare

Questions? Please email leadershipconsortium@nas.edu.

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