Dr. Bobak J. Mortazavi
Computer Science and Engineering
Texas A&M University
Abstract: Clinical models are often static in nature, homogenized in patient population and in patient comparisons and treatment decision making. As time varying, real time modeling becomes more prevalent, the need for remote health sensors and analytics, capable of capturing critical clinical biomarkers in real world environments, is necessary. This talk focuses on methods to advance the estimation of digital biomarkers for personalized monitoring and clinical diagnostics, in an effort to advance the integration of remote health analytics to longitudinal clinical outcomes models.
Biosketch: Dr. Bobak J. Mortazavi, is an Assistant Professor of Computer Science & Engineering at Texas A&M University. Prior to joining the computer science department, Dr. Mortazavi served as a postdoctoral associate in the Section of Cardiovascular Medicine, Department of Internal Medicine, at the Yale School of Medicine. His research focuses on the intersection of wearable technology, machine learning, and cardiovascular‐focused clinical outcomes research, to develop longitudinal, personalized models of health. His work has made important contributions in both modeling for translational clinical outcomes research in clinical settings as well as enabling wearable sensing technologies for personal, remote health monitoring.
Friday, Oct. 28, 2022
See details here.