The Swanson School of Engineering’s David Vorp and Timothy Chung are working in collaboration with the School of Medicine’s Nathan Liang to develop a new model to better predict patients at-risk for abdominal aortic aneurysm, the 15th leading cause of death in the U.S.
They received a $100,000 award from Precision Medicine Initiative for Commercialization for this effort.
The team is using tools to perform shape analysis and biomechanical simulations and will use these data to train a machine learning algorithm to classify different types of aneurysm outcomes. This classifier will be used to develop a predictive model that can help guide clinicians and determine the need for surgical intervention.
Abdominal aortic aneurysm occurs when the aorta weakens and begins to irreversibly dilate, like a slowly inflating balloon. If left untreated, the risk of rupture increases and has a 90 percent rate of mortality.