Upcoming Event: Babuška Forum

Physics-based simulation and AI in heart disease

Charley Taylor, UT Austin

Abstract

Patient-specific computational models of the cardiovascular system have generated significant interest since they were first introduced 30 years ago. Such models enable a new approach in medicine whereby predictive physics-based computational models can be used to evaluate and select alternate treatment strategies. Since they were first introduced 15 years ago, patient-specific models of coronary artery blood flow constructed from coronary CT angiography (cCTA) images leveraging deep learning A.I. methods and physics-based simulation have transformed the diagnosis of heart disease. These methods, based on computing flow and pressure in the coronary arteries, have been used for routine clinical decision making in thousands of hospitals that have served hundreds of thousands of patients in the United States, Europe, and Asia. Future opportunities for research in developing and applying computational methods for diagnosing and treating cardiovascular diseases will also be presented.

Biography

Dr. Taylor is the Moncrief Chair in Computational Medicine, Professor of Internal Medicine and Computational Engineering and Sciences, Director of the Center for Computational Medicine at the University of Texas, Austin. Dr. Taylor is also Founder and Member of the Board of HeartFlow Inc. and Chairman of Ebenbuild, GmBh. He was Chief Technology Officer then Chief Scientific Officer at HeartFlow from 2010 to 2023. He was Associate Professor of Bioengineering and Surgery at Stanford University from 1997 to 2010. He is internationally recognized for his pioneering work combining computer simulation, A.I. and medical imaging to aid in the diagnosis and treatment of
cardiovascular disease. Dr. Taylor published over 425 peer-reviewed papers and has over 300 patents. He received B.S., M.S. degrees in Mechanical Engineering and Mathematics from Rensselaer Polytechnic Institute and Ph.D. in Mechanical Engineering from Stanford University. Charles was elected into the U.S. National Academy of Engineering in 2024.