Stanford Center for Continuing Medical Education, Artificial Intelligence and Health Care Webinar (RECORDED), 5/5/2020 12:00:00 AM - 5/5/2023 12:00:00 AM, An Internet Enduring Material presented with the Stanford's Presence, National Academy of Medicine (NAM) and the U.S. Government Accountability Office (GAO) to 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.
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.
