Portability of an algorithm to identify rheumatoid arthritis in electronic health records. - Robert J. Carroll; William K. Thompson; Anne E. Eyler; Arthur M. Mandelin; Tianxi Cai; Raquel M. Zink; Jennifer A. Pacheco; Chad S. Boomershine; Thomas A. Lasko; Hua Xu 001; Elizabeth W. Karlson; Raúl G. Pérez; et al. (J. Am. Medical Informatics Assoc., 2012)

Automatic Prediction of Rheumatoid Arthritis Disease Activity from the Electronic Medical Records. - Chen Lin 002; Elizabeth W. Karlson; Helena Canhão; Timothy A. Miller; Dmitriy Dligach; Pei J. Chen; Raúl N. Pérez; Yuanyuan Shen; Michael E. Weinblatt; Nancy A. Shadick; Robert M. Plenge; Guergana Savova (AMIA, 2013)

Demonstrating the Advantages of Applying Data Mining Techniques on Time-Dependent Electronic Medical Records. - Uri Kartoun; Vishesh Kumar; Su-Chun Cheng; Sheng Yu 002; Katherine P. Liao; Elizabeth W. Karlson; Ashwin N. Ananthakrishnan; Zongqi Xia; Vivian S. Gainer; Andrew Cagan; Guergana Savova; Pei J. Chen; et al. (AMIA, 2015)

Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record. - Chen Lin 002; Elizabeth W. Karlson; Dmitriy Dligach; Monica P. Ramirez; Timothy A. Miller; Huan Mo; Natalie S. Braggs; Andrew Cagan; Vivian S. Gainer; Joshua C. Denny; Guergana K. Savova (J. Am. Medical Informatics Assoc., 2015)

Screening pregnant women for suicidal behavior in electronic medical records: diagnostic codes vs. clinical notes processed by natural language processing. - Qiu-Yue Zhong; Elizabeth W. Karlson; Bizu Gelaye; Sean Finan; Paul Avillach; Jordan W. Smoller; Tianxi Cai; Michelle A. Williams (BMC Medical Informatics Decis. Mak., 2018)

Evaluation of the Portability of Natural Language Processing-based Computable Phenotypes in the eMERGE Network. - Jennifer A. Pacheco; Luke V. Rasmussen; Ken Wiley; Thomas N. Person; David J. Cronkite; Sunghwan Sohn; Shawn N. Murphy; Justin H. Gundelach; Vivian S. Gainer; Victor M. Castro; Cong Liu 020; Todd Lingren; et al. (AMIA, 2021)

Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies. - Ning Shang; Atlas Khan; Fernanda Polubriaginof; Francesca Zanoni; Karla Mehl; David Fasel; Paul E. Drawz; Robert J. Carroll; Joshua C. Denny; Matthew A. Hathcock; Adelaide M. Arruda-Olson; Peggy L. Peissig; et al. (npj Digit. Medicine, 2021)

A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history. - Marc P. Maurits; Ilya Korsunsky; Soumya Raychaudhuri; Shawn N. Murphy; Jordan W. Smoller; Scott T. Weiss; Thomas W. J. Huizinga; Marcel J. T. Reinders; Elizabeth W. Karlson; Erik van den Akker 001; Rachel Knevel (J. Am. Medical Informatics Assoc., 2022)

The All of Us Research Program: Data quality, utility, and diversity. - Andrea H. Ramirez; Lina M. Sulieman; David J. Schlueter; Alese E. Halvorson; Jun Qian; Francis Ratsimbazafy; Roxana Loperena-Cortes; Kelsey R. Mayo; Melissa A. Basford; Nicole Deflaux; Karthik Muthuraman; Karthik Natarajan; et al. (Patterns, 2022)