Increasing Accessibility: Effectiveness of a Remote Artificial Intelligence Education Curriculum for International Medical Graduates

Abstract

Background

Applications of artificial intelligence (AI) in medicine are expanding every year. AI education is crucial to its appropriate use in healthcare; however, most US medical schools lack a dedicated AI curriculum. These resources are sparse for international medical graduates (IMGs). Using the Artificial Intelligence in Radiology Education (AIRE) curriculum, we assessed the radiology AI course's effectiveness in increasing the AI competency of IMGs.

Approach

AIRE curriculum features nine free YouTube lectures on AI in radiology. Participants watched lectures remotely on fundamental AI terms, methods, clinical applications and special topics. They completed a pre- and post-course e-survey and assessment. The survey assessed participants' prior AI experience, subjective knowledge and opinions on the need for AI in medical education. The assessment determined participants' knowledge of AI. Pre- and post-course assessment scores were compared using a Student's t-test to determine if the course increased participant knowledge of AI terms and applications.

Evaluation

Three hundred fifty-seven students from 28 countries enrolled in the course; 175 completed the course within the study period. Nearly all participants reported insufficient AI exposure in their radiology training (91.3%). Participants' knowledge of fundamental AI terms and methods increased after completion of the course, with an average pre-course assessment score of 6.5/15 and a post-course assessment score of 9.4/15 (p < 0.0001).

Implications

AIRE curriculum's effectiveness demonstrates that a remote education course is a viable model to bring accessible fundamental AI education to international medical students. Remote education curricula in medical AI can help mitigate disparities in AI education for lower resource medical programmes.