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Artificial Intelligence and Health Care presented by Stanford's Presence with NAM & GAO


Artificial Intelligence and Health Care presented by Stanford's Presence with NAM & GAO Banner

  • Overview
  • Faculty
  • Agenda
Add to Calendar Artificial Intelligence and Health Care presented by Stanford's Presence with NAM & GAO 4/30/2020 11:00:00 AM 4/30/2020 1:00:00 PM America/New_York For More Details: https://stanford.cloud-cme.com/AIHealthcare Description: A free live webinar, 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... false MM/DD/YYYY


Date & Location
Thursday, April 30, 2020, 11:00 AM - 1:00 PM EST

Overview
A free live webinar, 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.

Registration

This free webinar will be offered at 11:00 am - 1:00 pm PST (2:00 -4:00 pm ET). View the full agenda and learn more at HERE.

 


Credits
AMA PRA Category 1 Credits™ (2.00 hours), Non-Physician Participation Credit (2.00 hours)

Objectives
At the conclusion of this activity, learners should be able to:

  1. Evaluate how the use of AI in health care is poised to make transformative and disruptive advances in health care.
  2. Determine how AI may provide better healthcare, improved patient care experience, clinician well-being, lower costs, and health equity throughout.

Accreditation

This activity has been planned and implemented in accordance with the accreditation requirements and policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint providership of Stanford University School of Medicine and National Academy of Medicine (NAM) and the U.S. Government Accountability Office (GAO). The Stanford University School of Medicine is accredited by the ACCME to provide continuing medical education for physicians. 

Credit Designation
The Stanford University School of Medicine designates this Live Activity for a maximum of 2.00 AMA PRA Category 1 CreditsTM.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

The California Board of Registered Nursing recognizes that Continuing Medical Education (CME) is acceptable for meeting RN continuing education requirements as long as the course is certified for AMA PRA Category 1 CreditsTM (rn.ca.gov).  Nurses will receive a Certificate of Participation following this activity that may be used for license renewal. The provider number is: 0000751.


Additional Information

Accessibility Statement
 Stanford University School of Medicine is committed to ensuring that its programs, services, goods and facilities are accessible to individuals with disabilities as specified under Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Amendments Act of 2008.  

Cultural and Linguistic Competency
The planners and speakers of this CME activity have been encouraged to address cultural issues relevant to their topic area for the purpose of complying with California Assembly Bill 1195. Moreover, the Stanford University School of Medicine Multicultural Health Portal contains many useful cultural and linguistic competency tools including culture guides, language access information and pertinent state and federal laws.  You are encouraged to visit the Multicultural Health Portal: http://lane.stanford.edu/portals/cultural.html

Questions? Please email
[email protected].

For CME general questions, please contact 
     Ph: (650)-497-8554
     Email: [email protected]



The Stanford University School of Medicine adheres to ACCME Criteria, Standards and Policies regarding industry support of continuing medical education.   There are no relevant financial relationships with ACCME-defined commercial interests for anyone who was in control of the content of this activity.



Member Information
Role in activity
Nature of Relationship(s) / Name of Ineligible Company(s)
Glenn Cohen, JD
Faculty Director and James A. Attwood and Leslie Williams Professor of Law
Harvard Law School
Faculty
Nothing to disclose
M. Khair ElZarrad, PhD
FDA Center for Drug Evaluation and Research
Faculty
Nothing to disclose
Danielle Friend, PhD
Biotechnology Innovation Organization
Faculty
Nothing to disclose
Ken Getz, MBA
Tufts Center for the Study of Drug Development
Faculty
Nothing to disclose
Marelize Gorgens
World Bank Group
Faculty
Nothing to disclose
Karen Howard, MD
U.S. Government Accountability Office (GAO)
Faculty
Nothing to disclose
Faculty Photos
sonoo thadaney israni, mba
Executive Director
Stanford University Presence and The Program in Beside Medicine
Faculty
Nothing to disclose
Michael Matheny, MD
Vanderbilt University Medical Center
Faculty
Nothing to disclose
J. Michael McGinnis, MD
National Academy of Medicine
Faculty
Nothing to disclose
Rebecca Parkhurst, PA-C
U.S. Government Accountability Office (GAO)
Faculty
Nothing to disclose
Tim Persons, MD
U.S. Government Accountability Office (GAO)
Faculty
Nothing to disclose
Jack Resneck Jr., MD
UCSF and American Medical Association
Faculty
Nothing to disclose

Thursday, April 30, 2020

Welcome
11:00AM - 11:10AM
Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril: An NAM Special Publication
11:10AM - 11:25AM
Panel Discussion
11:25AM - 11:50AM
GAO Technology Assessment: Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development
11:50AM - 12:05PM
Panel Discussion
12:05PM - 12:30PM
Q&A
12:30PM - 1:00PM

 

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