Mimicking the Minds of M.D.s
Geoffrey Tison, M.D., M.P.H. Associate Professor Internal Medicine, Cardiology UC San Francisco
By Sarah Colwell
COMPUTATIONAL HEALTH
Artificial intelligence (AI) is poised to revolutionize healthcare, assisting doctors in diagnosing diseases, analyzing test results and predicting health risks. However, most AI systems focus on just one type of data at a time, limiting their ability to provide a comprehensive medical assessment. Unlike AI, doctors consider multiple factors—symptoms, medical history, lab results, and imaging scans—when making a diagnosis, leading to more accurate and informed decisions. Geoffrey Tison, M.D., MPH, a cardiologist and researcher, is working to bridge this gap. With support from the UC Noyce Initiative, his team is developing an AI system that aims to better mimic the way doctors think by integrating different types of patient data simultaneously. The hope is that simultaneously considering multiple medical tests will improve the AI model to recognize patterns that a single test might miss, providing more complete insights into a patient’s health. “Our goal is to provide AI with a greater breadth of data to allow it to think more like a doctor," Tison explained. “Instead of looking at just one piece of information, we want it to bring together different kinds of patient data—like blood tests and heart scans—to hopefully make a more accurate diagnosis.”
A Smarter AI for Detecting Heart Disease To test this approach, the research team is focusing on a common but serious heart condition called Heart Failure with Reduced Ejection Fraction. This occurs when the heart isn’t pumping blood as well as it should, making it harder for the body to get the oxygen and nutrients it needs. The AI system they developed was able to analyze two different types of patient data at the same time—something most medical AI models can’t do. However, while the system successfully learned from both data sources, it didn’t yet outperform separate AI models trained on each data type individually.
OUR GOAL IS TO PROVIDE AI WITH A GREATER BREADTH OF DATA TO ALLOW IT TO THINK MORE LIKE A DOCTOR.
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