The University of Cincinnati College of Medicine secured a $1.1 million grant from the American Medical Association to advance AI-powered physician training. The four-year project will focus on using artificial intelligence to deliver personalized, real-time feedback to approximately 600 medical trainees. This innovation aims to strengthen clinical reasoning and communication skills for improved patient care.
$1.1 Million AMA Grant Fuels AI in Medical Training
The $1.1 million grant from the AMA will support a four-year project focused on augmenting clinical reasoning and communication skills via real-time feedback. Researchers plan to extend the existing 2-Sigma AI platform, currently used for adaptive simulations, to analyze data from devices like eyeglasses and smartphones during patient interactions. This technology will then deliver personalized feedback through a smartphone application and heads-up displays within AI glasses. Approximately 600 medical students and residents across UC and Arizona State University will participate in testing the new AI algorithms.
The project will move from simulated environments to actual patient encounters, capturing a greater fraction of learning opportunities. This initiative aligns with the AMA’s broader $12 million investment in precision education, aiming to transform physician training through data-driven, personalized learning.
Sigma AI Platform Extends to Real-Time Feedback Delivery
The project will expand the existing 2-Sigma AI platform to deliver feedback in real-time, moving beyond simulations to actual clinical encounters. Investigators will employ AI algorithms to analyze interactions captured by devices like smartphones and specialized eyeglasses, providing trainees with personalized insights. This technology will deliver feedback via a smartphone application and a heads-up display, projecting vital information directly into a user’s field of vision. The aim is to transform patient interactions into learning opportunities by providing feedback on clinical reasoning and communication skills, ultimately refining how trainees connect with patients and diagnose complex cases. This initiative seeks to address the current lack of sufficient, high-quality feedback in medical training.
Just as data analytics transformed professional sports, precision education is poised to transform how we train physicians. Medical trainees spend thousands of hours in clinical settings but receive feedback on only a fraction of their patient encounters.
Laurah Turner, PhD
Precision Education Models Personalize Clinical Skill Development
This approach aims to address a gap in medical training where feedback on patient encounters is limited, despite the thousands of hours spent in clinical settings. This method promises to transform medical training by turning every patient encounter into a learning opportunity. The project utilizes ambient AI to capture data from trainees’ interactions, employing devices like eyeglasses and smartphones.
