Center for Predictive Computational Phenotyping

Description: 

This project develops improved algorithms for predictive computational phenotyping with applications to electronic health records, transcriptomics, epigenetics, medical imaging data and breast cancer. Research topics for all these applications include data management, dimensionality reduction, graphical models, value of information and high-throughput computation.

CS Collaborators: 

Miron Livny
Jignesh Patel
AnHai Doan
Mark Craven
Michael Newton
C David Page
Jerry Zhu
Sunduz Keles

Campus Collaborators: 

Paul Rathouz (BMI)

Funding: 

National Institutes of Health

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