Learning Effective Representations with Electronic Health Records

Fei Wang
Associate Professor
Department of Computer Science and Engineering, University of Connecticut
SERC 306
Monday, June 1, 2015 - 14:00
Data-Driven Healthcare (DDH) has aroused considerable interests from various research fields in recent years. Patient Electronic Health Records (EHR) is one of the major carriers for conducting DDH research. There are a lot of challenges on working directly with EHR, such as sparsity, high-dimensionality, and temporality. In this talk I will introduce my recent works on learning effective representations for EHR including: 1) a grouping scheme to get higher level EHR representations 2) temporal pattern extraction to explore the event temporalities of EHR. We will show various applications of those techniques including early prediction of the onset risk of chronic diseases and disease progression modeling.