Book Review: Transforming Legal Education: Learning and Teaching the Law in the Early Twenty-first Century. - Paul Maharg; John Mayer; Julian Webb; Abdul Paliwala (J. Inf. Law Technol., 2009)

Application of clinical text data for phenome-wide association studies (PheWASs). - Scott J. Hebbring; Majid Rastegar-Mojarad; Zhan Ye; John Mayer; Crystal Jacobson; Simon M. Lin (Bioinform., 2015)

bigNN: An open-source big data toolkit focused on biomedical sentence classification. - Ahmad Pahlavan Tafti; Ehsun Behravesh; Mehdi Assefi; Eric LaRose; Jonathan C. Badger; John Mayer; AnHai Doan; David Page; Peggy L. Peissig (IEEE BigData, 2017)

Use of Electronic Health Record to Predict Family Relationships for Phenome-wide Research. - Xiayuan Huang; Robert C. Elston; John Mayer; Zhan Ye; Yuqi He; David Page; Scott J. Hebbring (AMIA, 2018)

Applying family analyses to electronic health records to facilitate genetic research. - Xiayuan Huang; Robert C. Elston; Guilherme J. M. Rosa; John Mayer; Zhan Ye; Terrie E. Kitchner; Murray H. Brilliant; David Page; Scott J. Hebbring (Bioinform., 2018)

Machine learning for phenotyping opioid overdose events. - Jonathan C. Badger; Eric LaRose; John Mayer; Fereshteh S. Bashiri; David Page; Peggy L. Peissig (J. Biomed. Informatics, 2019)

Medical Big Data Analysis System to Discover Associations between Genetic Variants and Diseases. - Daehee Kim; Stephanie Gamboa; Vanessa Hernandez; Marlen Martinez-Lopez; Scott J. Hebbring; John Mayer; Jamie Fox (ICC, 2021)

E-Pedigrees: a large-scale automatic family pedigree prediction application. - Xiayuan Huang; Nicholas P. Tatonetti; Katie Larow; Brooke Delgoffee; John Mayer; David Page; Scott J. Hebbring (Bioinform., 2021)

Multisite evaluation of prediction models for emergency department crowding before and during the COVID-19 pandemic. - Ari J. Smith; Brian W. Patterson; Michael S. Pulia; John Mayer; Rebecca J. Schwei; Radha Nagarajan; Frank Liao; Manish N. Shah; Justin J. Boutilier (J. Am. Medical Informatics Assoc., 2023)