• Artificial Intelligence in Medicine

Invited SpeakersProfile Details

Zoran Obradovic
Zoran Obradovic Zoran Obradovic 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.

Biography

Zoran Obradovic 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. He has published more than 350 articles and is cited about 20,000 times (H-index 52). For more details see http://www.dabi.temple.edu/~zoran/.

All sessions by Zoran Obradovic

  • Day 3Wednesday, February 20th
Session 5 : AI and Knowledge Mining from Text, Clinical Data, and Bio-imaging (Chair - Xin Gao)
9:00 am

KEYNOTE LECTURE: Machine Learning for Decision Making in Healthcare

An overview of our ongoing projects aimed to facilitate predictive analytics in healthcare will be presented in this talk. Challenges and the proposed solutions will be discussed related to structured regression on multilayer networks, recovering network connectivity, modeling positive and negative influences, uncertainty propagation and effective integration of domain knowledge and big data. 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, discovering gene-disease interactions and assessing tolerance to viral infections.

Building 9 - Lecture hall 2 09:00 - 09:50 Details