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4pm
Free

CESG SEMINAR: “Systems for Clinical Outcomes Predictions”

September 15 @ 4:10 pm - 5:10 pm
WEB, Room 236-C,
Wisenbaker Engineering Building

Dr. Bobak Mortazavi Texas A & M University Abstract: The design of personal medical embedded systems for user-centric health monitoring involves an understanding of platform development for data collection, applications of machine learning for processing vast quantities of varying data, and an understanding of the underlying clinical questions these systems are trying to address. The interdisciplinary nature of these tasks requires an understanding of the clinical issues being addressed, and then developing specific systems and algorithms to address these, along with the unique challenges posed by each individual application. This talk focuses on an understanding of clinical data, the challenges posed by implementing machine learning techniques, understanding the differences between methods used in clinical outcomes predictions and those available to computer scientists, and then examines several open-ended case studies that have the potential for both algorithmic and embedded systems improvements. Bio: Dr. Bobak Mortazavi is an Assistant Professor in Computer Science and Engineering at Texas A&M. After receiving his bachelor’s degree from the University of California Berkeley, he earned his PhD in Computer Science from the University of California Los Angeles where he focused on the development of embedded systems for the Wireless Health Institute. Most recently, he was a postdoctoral associate, and then instructor, in the department of internal medicine, section of cardiology, at the Yale School of Medicine. He has recently focused on clinical research challenges in predictive models and comparative effectiveness techniques, in order to better address the challenges of personalized health monitoring, in the interest of developing personalized remote systems for clinical outcomes.

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