AI that teaches: An evidence-based GPT model to improve medical student understanding of pulmonary function tests - Aiyar, Anusha; Moon, Henry (Canadian Medical Education Journal / Revue canadienne de l'éducation médicale)

(untitled) (Canadian Medical Education Journal, 2025)
Implication StatementThis study explores the integration of an augmented Generative Pre-trained Transformer (GPT) tool with curated scientific sources to enhance the learning of pulmonary function test (PFT) interpretation in pre-clerkship medical education. Our findings suggest that this approach offers notable improvements in accuracy, reliability, and the quality of explanations compared to existing tools, such as Out-of-Box GPT and USMLE Q-Banks. The PFT learning assistant can support medical students in navigating common learning barriers, provide a personalized and scalable approach to evidence-based medical education