Grover Lab Grover Lab / AI in Medical Education
Research Area

AI in Medical Education

We study how AI should be used in medical education, including knowledge acquisition, practice, feedback, assessment, and faculty development. We focus on agents, source-grounded systems, and the skills clinicians need to build or supervise these tools.

AI in medical education at Grover Lab

Current work

We are studying where AI can be used across medical education paradigms, how agents should be used in training, how feedback and assessment can improve, and how clinicians should build or supervise these tools. That includes curriculum-linked systems such as SharpenEDU.

Selected publications

Integrating artificial intelligence into endoscopy training: opportunities, challenges, and strategies. Grover SC, Walsh CM. Lancet Gastroenterology & Hepatology. 2024. Gastrointestinal Endoscopy Clinics of North America article in press. Abstract link for a new 2026 publication in this research area. Comparison of the Impact of Wikipedia, UpToDate, and a Digital Textbook on Short-Term Knowledge Acquisition Among Medical Students. Scaffidi MA, Khan R, Wang C, et al. JMIR Medical Education. 2017. Video-based interventions to improve self-assessment accuracy among physicians: a systematic review. Pattni C, Scaffidi M, Li J, et al. PLOS One. 2023.

FAQ

Who leads this work? Samir C. Grover leads Grover Lab's work in AI in medical education at Scarborough Health Network and the University of Toronto.
What does Grover Lab study in AI in medical education? We study where AI can be used across medical education paradigms, how agents should be used in training, how feedback and assessment can improve, and how clinicians should build or supervise these tools.

Stay in the loop

Occasional essays on AI, simulation, and the future of medical education.