D&I Research Seminar

Decision Making in Healthcare by Learning from Structured Data and Qualitative Knowledge

ABSTRACT: An overview of our ongoing projects aimed to facilitate predictive analytics in healthcare will be presented in this talk. Challenges related to structured regression on multilayer networks, modeling positive and negative influences, uncertainty propagation and effective integration of domain knowledge and big data and the proposed solutions to these challenges will be discussed. The algorithms will be evaluated in the context of applications related to exploiting information extracted from electronic health records for identifying resources a patient would need for triage systems in emergency departments, estimating hospitalization cost, predicting admission and mortality rate for high impact diseases, identifying disease relationships and discovering gene-disease interactions.

BIO: Zoran Obradovic is an Academician at the Academia Europaea (the Academy of Europe) and a Foreign Academician at the Serbian Academy of Sciences and Arts. He is a L.H. Carnell Professor of Data Analytics at Temple University, Professor in the Department of Computer and Information Sciences with a secondary appointment in Department of Statistical Science, and is the Director of the Center for Data Analytics and Biomedical Informatics. His research interests include data science and complex networks in decision support systems. Zoran is the steering committee co-chair for the SIAM Data Mining conference. He is also the editorial board member at 13 journals and was the general chair, program chair or a track chair for 11 international conferences. He has published more than 350 articles and is cited more than 20,000 times (H-index 54). 

For more details see http://www.dabi.temple.edu/~zoran

Thursday, March 8, 2018 from 11 a.m. to 12:30 p.m.
Peter B. Lewis Building, Room 05
11119 Bellflower Road
Cleveland, OH 44106-7235
United States
Speaker(s): Zoran Obradovic, PhD, Temple University
Sponsored by: Design and Innovation
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