Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study.

ABSTRACT:

Background

As artificial intelligence and machine learning become increasingly influential in clinical practice, it is critical for future physicians to understand how such novel technologies will impact the delivery of patient care.

Objective

We describe 2 trainee-led, multi-institutional datathons as an effective means of teaching key data science and machine learning skills to medical trainees. We offer key insights on the practical implementation of such datathons and analyze experiences gained and lessons learned for future datathon initiatives.

Methods

We detail 2 recent datathons organized by MDplus, a national trainee-led nonprofit organization. To assess the efficacy of the datathon as an educational experience, an opt-in postdatathon survey was sent to all r

SUBMITTER: Yao MS 

PROVIDER: S-EPMC12017604 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature