LINK:  https://bswhealth.webex.com/bswhealth/j.php?MTID=m6dda7d98e1a92001822b4fbd605d4185

OBJECTIVES: Upon completion of this activity, the participant should be able to:  (1) Review commonalities and distinctions between artificial intelligence (Al), machine learning (ML), and predictive analytics. (2) Explain the current and  evolving role of Al in transplantation. (3) Select a case for an increased use of AI in organ allocation policies and organ offer decision-making. (4) Discuss how Al has the potential to remove the “ disconnect” between policies and decision making to improve system efficiency and reduce organ non-use.

FACULTY DISCLOSURE: Darren Stewart, M.S, is a consultant for Veloxis Pharmaceuticals and Aditxt, Inc. Companies.

PLANNER DISCLOSURE: James Trotter, MD, Sumeet Asrani, MD, Gregory McKenna, MD, and Kathy Brown, RN, CCTC, have no relevant financial relationship(s) to disclose with companies whose primary business is producing, marketing, selling, re-selling, or distributing healthcare products used by or on patients.

All relevant financial relationships have been mitigated.

ACCREDITATION: The A. Webb Roberts Center for Continuing Medical Education of Baylor Scott & White Health is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

DESIGNATION:  The A. Webb Roberts Center for Continuing Medical Education of Baylor Scott & White Health designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CEPTC Credit: The American Board for Transplant Certification (ABTC) has been applied for educational offering for up to 1 Category 1 Continuing Education Point for Transplant Certification (CEPTCs).

For information, please contact Karina Pena at [email protected]