Paper 13410-509
Paper 13410-509
Machine learning in neuroimaging: Understanding heterogeneity of neurologic diseases and building personalized imaging-AI biomarkers (Keynote Presentation)
20 February 2025 • 9:20 AM - 10:00 AM PST | Town & Country B/C
Abstract
Machine learning has transformed medical imaging in general, and neuroimaging in particular, during the past two decades. We review our work in this field, starting with early contributions on developing personalized predictive markers of brain change in aging and Alzheimer’s Disease, and moving to recent weakly-supervised deep learning methods, aiming to dissect heterogeneity of brain change in neurodegenerative and neuropsychiatric diseases, as well as in brain cancer. We show that disease-related brain changes can follow multiple trajectories and patterns, which have distinct clinical and genetic correlates, thereby suggesting a dimensional approach to capturing brain phenotypes, using machine learning methods.
Presenter
Christos Davatzikos
Penn Medicine (United States)
Christos Davatzikos is the Wallace T. Miller Sr. Professor of Radiology at the University of Pennsylvania, and Director of the AI2D Center (https://ai2d.med.upenn.edu/). Dr. Davatzikos holds a secondary appointment in DBEI and in Electrical and Systems Engineering at Penn, as well as at the Bioengineering and Applied Mathematics graduate groups. He obtained his undergraduate degree from the National Technical University of Athens, Greece in 1989; and his Ph.D. degree from Johns Hopkins in 1994 on a Fulbright scholarship. Dr. Davatzikos then joined the faculty in Radiology, and later in Computer Science, where he founded and directed the Neuroimaging Laboratory. In 2002, Dr. Davatzikos moved to Penn, where he founded and directed the section of Biomedical Image Analysis. His interests are in medical image analysis and machine learning. He oversees a diverse research program focusing on AI methods in Neuroimaging, as well as its application to clinical studies on aging and Alzheimers.