Download Location: Fakultet organizacionih nauka Univerziteta u Beogradu

Location: Fakultet organizacionih nauka Univerziteta u Beogradu (sala 201)
Time: 17. June, 2013 13:00
Title:
Mortality Reduction in Acute Inflammation by Improved Prediction of Patients’ Response to
Treatment
Speaker:
Zoran Obradovic,
Director, Data Analytics and Biomedical Informatics Center,
Professor, Computer and Information Sciences Department,
Professor, Statistics Department, Fox School of Business (secondary appointment),
Temple University
Abstract:
Uncontrolled inflammation accompanied by an infection that results in septic shock is the most
common cause of death in intensive care units and the 10th leading cause of death overall. In
principle, spectacular mortality rate reduction can be achieved by early diagnosis and accurate
prediction of response to therapy. This is a very difficult objective due to the fast progression
and complex multi-stage nature of acute inflammation. Our ongoing DARPA DLT project is
addressing this challenge by development and validation of effective predictive modeling
technology for analysis of temporal dependencies in complex data related to acute
inflammation. This lecture will provide an overview of the results of our project obtained over
the last several months and will discuss in more detail results that will be published a few days
after this talk at ICML and CIBB conferences in Atlanta, GA and in Nice, France. In particular, a
Gaussian Conditional Random Field model, as well as a mixture of experts model that identifies
stages of the acute inflammation state and builds specialized predictors for each stage will be
presented. In conducted large-scale experiments, our approach outperformed alternatives in
accuracy and it also identified three stage-specific expert models that can play an important role
in improving acute inflammation treatment.
This is joint research with Vladan Radosavljevic and Kosta Ristovski, who are postdoctoral
associates at my laboratory.
Biography:
Zoran Obradovic’s research interests include data mining, machine learning and complex
networks applications. He is the executive editor at the journal on Statistical Analysis and Data
Mining, which is the official publication of the American Statistical Association and is an editorial
board member at eleven journals. He is general co-chair for 2013 and 2014 SIAM International
Conference on Data Mining and was the program or track chair at many data mining and
biomedical informatics conference. His data analytics work is published in more than 260
articles and is cited more than 11,500 times (H-index 43). For more details see
http://www.dabi.temple.edu/~zoran/