Artificial Intelligence in Medicine
Overview
Needs Statement
Gastroenterologists, hepatologists, transplant surgeons, internists, advanced practice providers, fellows, residents, and medical students need to receive regular updates on recent advances in the field of Hepatology and Liver Transplantation. The series will highlight new developments in all areas related to liver diseases, changing selection criteria for transplantation, emerging transplantation techniques, and improved immunosuppressive therapies to minimize graft loss and other complications. The series aims to expand the knowledge of learners, promote current clinical and surgical best practices, enhance the quality of hepatology care, improve patient outcomes, and direct future research.
Target Audience
Physicians, medical students, fellows, residents, and other health professionals.
Learning Objectives
At the conclusion of the session, the participants should be able to:
- Define artificial intelligence and machine learning.
- Describe big data.
- Delineate potential applications for artificial intelligence and big data in the field of solid organ transplantation.
Accreditation
Baylor College of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
Baylor College of Medicine designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Available Credit
- 1.00 AMA PRA Category 1 Credit™
- 1.00 Participation
Register/Take course
Thank you for reviewing this Baylor College of Medicine on-demand activity. In order to complete the evaluation and claim credit for your participation, please select the appropriate payment option above. After payment has been completed, you will receive an email confirmation and receipt.
For any questions, contact cpd@bcm.edu.