Importance of multi-modal approaches to effectively identify cataract cases from electronic health records. - Peggy L. Peissig; Luke V. Rasmussen; Richard L. Berg; James G. Linneman; Catherine A. McCarty; Carol Waudby; Lin Chen; Joshua C. Denny; Russell A. Wilke; Jyotishman Pathak; David Carrell; Abel N. Kho; et al. (J. Am. Medical Informatics Assoc., 2012)

Next-Generation Analysis of Cataracts: Determining Knowledge Driven Gene-Gene Interactions Using Biofilter, and Gene-Environment Interactions Using the PhenX Toolkit. - Sarah A. Pendergrass; Shefali S. Verma; Emily Rose Holzinger; Carrie Moore; John R. Wallace; Scott M. Dudek; Wayne Huggins; Terrie E. Kitchner; Carol Waudby; Richard L. Berg; Catherine A. McCarty; Marylyn D. Ritchie (Pacific Symposium on Biocomputing, 2013)

Development and validation of an electronic phenotyping algorithm for chronic kidney disease. - Girish N. Nadkarni; Omri Gottesman; James G. Linneman; Herbert S. Chase; Richard L. Berg; Samira Farouk; Vaneet Lotay; Stephen B. Ellis; George Hripcsak; Peggy L. Peissig; Chunhua Weng; Rajiv Nadukuru; et al. (AMIA, 2014)

Relational machine learning for electronic health record-driven phenotyping. - Peggy L. Peissig; Vítor Santos Costa; Michael Caldwell; Carla Rottscheit; Richard L. Berg; Eneida A. Mendonça; David Page (J. Biomed. Informatics, 2014)

A novel method for studying the temporal relationship between type 2 diabetes mellitus and cancer using the electronic medical record. - Adedayo A. Onitilo; Rachel V. Stankowski; Richard L. Berg; Jessica M. Engel; Gail M. Williams; Suhail A. Doi (BMC Medical Informatics Decis. Mak., 2014)

SCCS for Detection of Differences in Brand and Generic Adverse Drug Events. - Jonathan C. Badger; Eric R. LaRose; Ross Kleiman; Richard L. Berg; James G. Linneman; Richard Hansen; David Page; Peggy L. Peissig (CRI, 2017)

Quantifying predictive capability of electronic health records for the most harmful breast cancer. - Yirong Wu; Jun Fan; Peggy L. Peissig; Richard L. Berg; Ahmad Pahlavan Tafti; Jie Yin; Ming Yuan 001; David Page; Jennifer Cox; Elizabeth S. Burnside (Image Perception, Observer Performance, and Technology Assessment, 2018)

High-Throughput Machine Learning from Electronic Health Records. - Ross S. Kleiman; Paul S. Bennett; Peggy L. Peissig; Richard L. Berg; Zhaobin Kuang; Scott J. Hebbring; Michael D. Caldwell; David Page (CoRR, 2019)