EHR-based Phenotyping Project

This project is developing novel machine-learning approaches and software for automatically phenotyping subjects from their electronic health records (EHRs), and for predicting clinically relevant phenotypes before they are exhibited. These approaches will be used to identify cases and controls for various studies, identify significant risk factors for diseases and disorders of interest, and predict risk for specific clinical events.

Related CPCP Publications

Privacy-preserving ridge regression with only linearly-homomorphic encryption. Giacomelli I , Jha S, Joye M, Page CD, Yoon K. Proceedings of Applied Cryptography & Network Security (ACNS), 2018

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Using machine learning algorithms to predict risk for development of calciphylaxis in patients with chronic kidney disease. Kleiman R, LaRose E, Badger J, Page D, Caldwell M, Clay J, Peissig P. Proceedings of the AMIA Informatics Summit, 2018

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Quantifying predictive capability of electronic health records for the most harmful breast cancer. Wu Y, Fan J, Peissig P, Berg R, Tafti P, Yin J, Yuan M, Page D, Cox J, Burnside E. Proceedings of SPIE Medical Imaging, 2018

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Applying family analyses to electronic health records to facilitate genetic research. Huang X, Elston RC, Rosa GJ, Mayer J, Ye Z, Kitchner T, Brilliant MH, Page D, Hebbring SJ. Bioinformatics 34(4):635–642, 2018

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Adverse drug event discovery using biomedical literature: A big data neural network adventure. Tafti AP, Badger J, LaRose E, Shirzadi E, Mahnke A, Mayer J, Ye Z, Page D, Peissig P. JMIR Medical Informatics 5(4):e51, 2017

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David Page


Mark Craven

Peggy Peissig

Ross Kleiman

Akshay Sood

Zhaobin "Charles" Kuang

Alex Cobian


CPCP 2017 Retreat: Entity Matching Using Magellan - Matching Drug Reference Tables Symposium Video

CPCP 2017 Retreat: Improved Methods for Discovering Adverse Drug Events from EHR Data Symposium Video

CPCP 2017 Retreat: Privacy-Preserving Machine Learning Symposium Video

CPCP Retreat 2016: Entity Matching for EHR- and Transcriptome-based Phenotyping Symposium Video

CPCP Retreat 2016: Using Active Learning to Phenotype Electronic Medical Records Symposium Video

CPCP Retreat 2016: High-Throughput Predictive Phenotyping from Electronic Health Records Symposium Video

Small Talks about Big Data: Predicting Health Events from EHRs Using Machine Learning Small Talk Video