Seminar - Jimeng Sun, PhD - Building Scalable Predictive Modeling Platform for Healthcare Applications

ABSTRACT

As the adoption of electronic health records (EHRs) has grown, EHRs are now composed of a diverse array of data, including structured information and unstructured clinical progress notes. Two unique challenges need to be addressed in order to utilize EHR data in clinical research and practice:

1. Computational phenotyping: How to turn complex and messy EHR data into meaningful clinical concepts or phenotypes?
2. Predictive modeling: How to develop accurate predictive models using longitudinal EHR data?

To address these challenges, I will present our approaches using a case study on early detection for heart failure. For computational phenotyping, we present EHR data as data as inter-connected high-order relations i.e. tensors (e.g. tuples of patient-medication-diagnosis, patient-lab, and patient-symptoms), and then develop expert-guided sparse nonnegative tensor factorization for extracting multiple phenotype candidates from EHR data. Most of the phenotype candidates are considered clinically meaningful and with great predictive power. For predictive modeling, I will present how using deep learning to model temporal relations among events in EHR improved model performance in predicting heart failure (HF) diagnosis compared to conventional methods that ignore temporality.

BIO

Jimeng Sun is an Associate Professor of School of Computational Science and Engineering at College of Computing in Georgia Institute of Technology. Prior to joining Georgia Tech, he was a research staff member at IBM TJ Watson Research Center. His research focuses on health analytics using electronic health records and data mining, especially in designing novel tensor analysis and similarity learning methods and developing large-scale predictive modeling systems. He has published over 70 papers, filed over 20 patents (5 granted). He has received ICDM best research paper award in 2008, SDM best research paper award in 2007, and KDD Dissertation runner-up award in 2008. Dr. Sun received his B.S. in Computer Science from Hong Kong University of Science and Technology in 2002, and PhD in Computer Science from Carnegie Mellon University in 2007.