To advance the integration of artificial intelligence (AI) into medical education, PUMCH recently welcomed Professor David Beiser and Dr. Nicholas G. Ludmer from the University of Chicago, along with 13 physicians and medical students from the University of Michigan and NewYork-Presbyterian Hospital. The visit centered on a series of activities exploring innovation and AI applications in medical education, including a symposium and a hands-on workshop. PUMCH Vice President Wu Wenming presented certificates of appreciation to Professor Beiser and Dr. Ludmer. The visit deepened cross-cultural exchanges, strengthened international collaboration, and offered fresh perspectives on building more effective and scientifically grounded models of medical training.

On April 27th, a symposium on medical talent development brought together cardiologists and cardiac surgeons from PUMCH and Professor Beiser and Dr. Ludmer for in-depth discussion on AI in medical education. PUMCH introduced its "PUMCH-GENESIS" large language model, highlighting its potential in the diagnosis and research of rare diseases and its advantages in teaching residents about both common and rare conditions — leaving a strong impression on the visiting delegation. The experts all believed that AI is increasingly becoming a valuable tool in clinical teaching, but its wider adoption also poses new challenges for residency training models and effectiveness. Clinical educators should guide young physicians in using AI thoughtfully and responsibly — guarding against over-reliance and ensuring it does not erode the depth of clinical reasoning.

The following Hands-on Workshop on "Building Interactive AI Teaching Assistants with LLMs" was led by Professor Beiser and Dr. Ludmer. Eleven medical students from the University of Michigan and two clinicians from NewYork-Presbyterian Hospital were paired with 36 PUMCH faculty members and students in mixed groups to learn through cases. The session covered AI applications in supporting clinical decision-making, optimizing learning pathways, and reshaping teaching models — offering a glimpse into AI's broad potential in medicine. Participants drew on their own experiences to explore how AI might be applied in both education and clinical practice.