{"id":49417,"date":"2025-03-27T15:42:42","date_gmt":"2025-03-27T19:42:42","guid":{"rendered":"https:\/\/alumni.cornell.edu\/cornellians\/?p=49417"},"modified":"2025-03-27T15:42:42","modified_gmt":"2025-03-27T19:42:42","slug":"ai-med-students","status":"publish","type":"post","link":"https:\/\/alumni.cornell.edu\/cornellians\/ai-med-students\/","title":{"rendered":"Digital Docs: How AI is Helping Train Medical Students"},"content":{"rendered":"\n

Simulating telehealth, the tech lets future physicians\u2014at Cornell and elsewhere\u2014hone their diagnosis and communication skills<\/p>\n\n\n\n

Editor\u2019s note: This story was condensed from <\/em>a feature<\/em><\/a> in the<\/em> Cornell Chronicle.<\/p>\n\n\n\n

By Patricia Waldron<\/strong><\/p>\n\n\n\n

At Weill Cornell Medicine<\/a>, students have a new tool for polishing their bedside manner and making a diagnosis: an AI-powered virtual patient that simulates the doctor-patient interaction.<\/p>\n\n\n\n

The simulator, called MedSimAI<\/a>, has a text-based chat function and a voice conversation mode that approximates a telehealth visit. It gives students a low-stress setting to practice communicating with empathy and to reason through potential diagnoses.<\/p>\n\n\n\n

Researchers in the Bowers College of Computing and Information Science<\/a> are developing the platform in collaboration with medical professionals at Weill Cornell Medicine, Yale, and the University of California, San Francisco.<\/p>\n\n\n\n

Traditionally, medical students develop their patient interviewing skills through graded interactions with actors posing as patients in a simulation clinic. These Objective Structured Clinical Examinations (OSCEs) are expensive and time-consuming, however, which limits students\u2019 practice opportunities.<\/p>\n\n\n\n

<\/p>\n\n\n\n

\n

Researchers have attempted to simulate this experience digitally, but earlier chatbots did a poor job producing realistic patient responses, and pricey virtual reality-based systems did little to improve accessibility.<\/p>\n\n\n\n

\u201cSimulation-based learning is known to be highly effective for training future physicians, nurses, veterinarians, and other clinical professionals,\u201d says Rene Kizilcec<\/a>, associate professor of information science in Bowers and lead researcher on MedSimAI.<\/p>\n\n\n\n

\u201cBuilding on the latest advances in generative AI, we can offer students unlimited opportunities to practice their clinical communication and reasoning skills with immediate feedback and just the right level of realism.\u201d<\/p>\n<\/div>

\"Prof.
Prof. Rene Kizilcec.<\/figcaption><\/figure><\/div>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

The MedSimAI platform uses state-of-the-art large language models to generate a patient\u2019s responses based on a script provided by medical educators. It also has a second AI model that evaluates the student\u2019s performance, using the same rubric that experts use to score OSCEs.<\/p>\n\n\n\n

The model gives immediate feedback\u2014instead of waiting days or weeks with traditional OSCEs\u2014and even highlights specific comments that showed empathy or questions that lacked key details.<\/p>\n\n\n\n

Dr. MacKenzi Nicole Preston<\/a>\u2014associate director of Weill Cornell Medicine\u2019s Clinical Skills Center, where students practice with robotic mannequins and actors\u2014is working with Kizilcec\u2019s team to test the efficacy of MedSimAI as part of the curriculum. She says feedback from the students has been positive.<\/p>\n\n\n\n

The AI model gives immediate feedback, and even highlights specific comments that showed empathy or questions that lacked key details.<\/p><\/blockquote><\/figure>\n\n\n\n

\u201cPart of the physician\u2019s job is being able to communicate in a way that helps patients to be comfortable,\u201d says Preston, also an assistant professor of clinical pediatrics.<\/p>\n\n\n\n

But in addition to showing compassion, she says, \u201cit\u2019s essential that physicians learn to ask the right questions and interpret the information they get in a way that brings them closer to the truth.\u201d<\/p>\n\n\n\n

Yann Hicke, MEng \u201915, a doctoral student in computer science, has been building the platform and developing specific cases to help students prepare for their OSCEs.<\/p>\n\n\n\n

\"a
Hicke (right) talks to an AI-generated “patient.”<\/figcaption><\/figure>\n\n\n\n

\u201cThe platform provides the opportunity for \u2018deliberate practice,\u2019 where students can see their strengths and weaknesses and seek out specific cases that let them practice skills they are lacking,\u201d he says.<\/p>\n\n\n\n

This year, first-year students took a complete medical history through MedSimAI as part of a full-day simulation treating a patient with rheumatic heart disease, while second-years used it in their pediatric rotation to practice taking a child\u2019s history from a parent.<\/p>\n\n\n\n

\u201cIt\u2019s very natural to use,\u201d says first-year Kellen Vu. \u201cIt\u2019s voice-based, so that lets the conversation flow smoothly. I think it\u2019s important for practicing your bedside manner, because tone and phrasing matter a lot in real life with patients.\u201d<\/p>\n\n\n\n

Top: First-year med student Shazain Ahmed Khan practices patient interaction with MedSimAI. (All images provided)<\/em><\/p>\n\n\n\n

Published March 27, 2025<\/p>\n\n\n\n

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