Location

Please check the individual session for location or broadcast availability.  

Frequency

Weekly

Series Director

Ruchi Gaba, MD

Target Audience and Needs

Faculty in clinical, research, and educational roles often face challenges in integrating artificial intelligence (AI) into workflows because of limited foundational knowledge, ethical concerns, and insufficient exposure to practical tools that enhance efficiency and innovation. This series aims to bridge the gap between theoretical knowledge and real-world clinical practice, promote the use of research tools such as literature review automation and data analytics, and advance the application of AI-driven educational methods synergistically with the Learning Health System.  By focusing on practical applications, ethical challenges, and future innovations, the series seeks to break down barriers to the implementation of AI and to foster innovation and collaboration.

Educational Methods

Educational methods will include lectures, case presentations, literature review, and panel discussion.

Objectives

At the conclusion of the sessions, the participants should be able to:

• Define artificial intelligence (AI) and describe its foundational principles, applications, potential, and limitations in healthcare.
• Identify and utilize AI tools to streamline clinical workflows, enhance curriculum design, and improve patient care.
• Develop strategic approaches to seamlessly integrate cutting-edge AI solutions into academic medicine.
• Analyze ethical challenges related to AI and apply strategies to ensure responsible implementation of AI in healthcare.
• Implement AI-based data analytic tools to streamline research workflows, improve data accuracy, and accelerate the discovery process.

Evaluation

Participants may be asked to complete a session evaluation.

Accreditation/Credit Designation

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™.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Series Coordinator