IEEE SP Atlanta - From Prediction of Life Threatening Events to Optimization of Treatment Strategies: An Overture to a Continuously Learning Healthcare System

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You are invited to join us for a technical lecture of the IEEE Signal Processing Chapter of Atlanta. The chapter is honored to host Dr. Shamim Nemati from Emory University. Dr. Nemati is an Assitant Professor at the Emory Department of Biomedical Informatics and he will present a lecture titled: 

From Prediction of Life Threatening Events to Optimization of Treatment Strategies: An Overture to a Continuously Learning Healthcare System

This meeting is part of the annual Signal Processing Seminar Series.

 



  Date and Time

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  • 85 Fifth Street NW
  • Atlanta, Georgia
  • United States 30308
  • Building: Technology Square Research Building (TSRB)
  • Room Number: 125
  • Click here for Map

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  Speakers

Shamim Nemati, PhD
Shamim Nemati, PhD of Emory University, Emory Department of Biomedical Informatics

Topic:

From Prediction of Life Threatening Events to Optimization of Treatment Strategies

Clinical medical decision-making is an imperfect science influenced by numerous factors including: incomplete knowledge of critical care physiology and varied patient response to standard of care. Most patient care protocols are derived from population-based studies that often rely on low-dimensional and static patient phenotypes. As an example, we consider the problem of early prediction and treatment of Sepsis; the leading causes of morbidity and mortality in critically ill patients and the most expensive condition by healthcare spending. The major tenet of sepsis care is prompt recognition and initiation of treatment, however, no clinically validated system exists for accurate, real-time prediction of sepsis onset, and considerable controversies remain concerning the effectiveness of various treatment options for septic patients. In this talk, I will discuss how modern signal processing and machine learning tools in association with clinical big data can be adopted to improve early prediction of sepsis and design effective treatment strategies.

Biography:

Shamim Nemati obtained his Ph.D. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2013. While at MIT, he was a member of the Laboratory for Computational Physiology and Clinical Inference, and a research fellow at the Brigham and Women's Hospital and the Harvard Medical School, where he held a National Research Service Award (NRSA). Upon completion of his graduate studies, Dr. Nemati joined the Harvard Intelligent Probabilistic Systems group as a James S. McDonnell postdoctoral fellow in complex systems, where he worked on advanced machine learning algorithms capable of meaningfully summarizing large volumes of continuously measured patient data, with the goal of timely prediction of potentially life threatening clinical events. Dr. Nemati has worked and published on several areas of research, including advanced signal processing and machine learning techniques, radar meteorology, computational neuroscience/brain machine interface, physiological control systems, predictive monitoring in intensive care unit, and nonlinear and nonstationary multidimensional time-series analysis in massive temporal biomedical databases; resulting in over 60 peer-reviewed publications. He is currently an assistant Professor of Biomedical Informatics at the Emory School of Medicine, and a recipient of NIH Early Career Development Award (K01) in biomedical Big Data science, focused on development of advanced analytic techniques for prediction of adverse events in the ICU.

Shamim Nemati, PhD of Emory University, Emory Department of Biomedical Informatics

Topic:

From Prediction of Life Threatening Events to Optimization of Treatment Strategies

Biography:





Agenda

Refreshments will be served at 11:45

Lecture to start at 12:00