Artificial Intelligence and Clinical Diagnosis: Considerations for the Future of Medical Practice
Faculty and trainees within the Department of Medicine who are involved in the care of patients need to receive regular updates on recent advances and guidelines in the field of internal medicine. Clinical scenarios will be used to review the current management of common medical conditions, including chronic pain and opioid abuse. Multidisciplinary sessions will also be used to educate learners about human trafficking and the role of physicians in identifying and assisting victims in the community. The overall aim of the series is to advance clinical knowledge, enhance the quality of patient care, and improve treatment outcomes.
Physicians, medical students, fellows, and residents.
At the conclusion of the session, the participants should be able to:
Define the terms generative artificial intelligence (AI) and large language model.
Describe advantages and limitations of current applications of AI in clinical diagnosis.
Recognize why judging the accuracy of diagnosis can be challenging in AI implementation.
Describe a framework for integration of AI into modern clinical practice.
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 enduring material activity for a maximum of 1.00 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
- 1.00 AMA PRA Category 1 Credit™
- 1.00 Participation