Integrating Artificial Intelligence in the Medical Curriculum: Approaches and Strategies

Area of Science:

• Medical Education
• Artificial Intelligence in Medicine (AIM)

Background:

• AIM integration into medical curricula is essential but challenging.
• Balancing theoretical knowledge with practical application is a key hurdle.

Purpose of the Study:

• To detail the development, implementation, and evaluation of an AIM course for medical students.
• To identify challenges and provide insights for future AIM curriculum design.

Main Methods:

• Course development aligned with institutional goals and addressed material scarcity.
• Implementation involved teaching theoretical concepts and practical applications.
• Evaluation focused on assessing the gap between theoretical understanding and practical application.

Main Results:

• Students demonstrated a gap between understanding AIM theory and applying it to medical scenarios.
• Ontologies and Natural Language Processing (NLP) were identified as particularly challenging areas.
• Course revisions included expanded content on formal logic and prompt engineering.

Conclusions:

• The first year of AIM course implementation provided valuable lessons for curriculum refinement.
• Interdisciplinary collaboration is vital for successful AIM integration in medical education.
• This experience offers a roadmap for preparing future physicians to utilize new technologies effectively.