Reducing patient re-identification risk for laboratory results within research datasets. - Ravi V. Atreya; Joshua C. Smith; Allison B. McCoy; Bradley A. Malin; Randolph A. Miller (J. Am. Medical Informatics Assoc., 2013)

Phenome-Wide Association Studies Using NLP-Derived Concepts. - Pedro L. Teixeira; Robert J. Carroll; Lisa Bastarache; Peter Speltz; Joshua C. Smith; Joshua C. Denny (AMIA, 2014)

Evaluation of a Novel System to Enhance Clinicians' Recognition of Preadmission Adverse Drug Reactions. - Joshua C. Smith; Qingxia Chen; Joshua C. Denny; Dan M. Roden; Kevin B. Johnson; Randolph A. Miller (Appl. Clin. Inform., 2018)

Real-time Clinical Note Monitoring to Detect Conditions for Follow-up: a Case Study of Clinical Trial Enrollment in Drug-induced Torsades de Pointes and Stevens-Johnson Syndrome. - Sarah DeLozier; Peter Speltz; Jason Brito; Leigh Anne Tang; Janey Wang; Joshua C. Smith; Dario A. Giuse; Elizabeth Phillips; Kristina Williams; Teresa Strickland; Giovanni Davogustto; Dan M. Roden; et al. (AMIA, 2020)

Natural Language Processing and Machine Learning to Enable Clinical Decision Support for Treatment of Pediatric Pneumonia. - Joshua C. Smith; Ashley Spann; Allison B. McCoy; Jakobi A. Johnson; Donald H. Arnold; Derek J. Williams; Asli Weitkamp (AMIA, 2020)

Predictive Model for Inpatient Mortality. - Joshua C. Smith; Allison B. McCoy; John A. Morris; Asli Weitkamp (AMIA, 2021)

Natural language processing to identify lupus nephritis phenotype in electronic health records. - Yu Deng; Jennifer A. Pacheco; Anh H. Chung; Chengsheng Mao; Joshua C. Smith; Juan Zhao 003; Wei-Qi Wei; April Barnado; Chunhua Weng; Cong Liu 020; Adam Cordon; Jingzhi Yu; et al. (CoRR, 2021)

Real-time clinical note monitoring to detect conditions for rapid follow-up: A case study of clinical trial enrollment in drug-induced torsades de pointes and Stevens-Johnson syndrome. - Sarah DeLozier; Peter Speltz; Jason Brito; Leigh Anne Tang; Janey Wang; Joshua C. Smith; Dario A. Giuse; Elizabeth Phillips; Kristina Williams; T. Stephen Strickland; Giovanni Davogustto; Dan M. Roden; et al. (J. Am. Medical Informatics Assoc., 2021)

ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes. - Juan Zhao 003; Monika E. Grabowska; Vern Eric Kerchberger; Joshua C. Smith; H. Nur Eken; QiPing Feng; Josh F. Peterson; S. Trent Rosenbloom; Kevin B. Johnson; Wei-Qi Wei (J. Biomed. Informatics, 2021)

Data-driven automated classification algorithms for acute health conditions: Applying PheNorm to COVID-19 disease. - Joshua C. Smith; Daniel Park; Jill Whitaker Bey; Michael F. McLemore; Elizabeth Hanchrow; Dax Westerman; Joshua Osmanski; Robert Winter 003; Arvind Ramaprasan; Ann Kelley; Mary Shea; David J. Cronkite; et al. (AMIA, 2022)

Do electronic health record systems "dumb down" clinicians? - Genevieve B. Melton; James J. Cimino; Christoph U. Lehmann; Patricia Sengstack; Joshua C. Smith; William M. Tierney; Randolph A. Miller (J. Am. Medical Informatics Assoc., 2022)

Natural language processing to identify lupus nephritis phenotype in electronic health records. - Yu Deng; Jennifer A. Pacheco; Anika S. Ghosh; Anh H. Chung; Chengsheng Mao; Joshua C. Smith; Juan Zhao 003; Wei-Qi Wei; April Barnado; Chad Dorn; Chunhua Weng; Cong Liu 020; et al. (BMC Medical Informatics Decis. Mak., 2022)

Data-driven automated classification algorithms for acute health conditions: applying PheNorm to COVID-19 disease. - Joshua C. Smith; Brian D. Williamson; David J. Cronkite; Daniel Park; Jill M. Whitaker; Michael F. McLemore; Joshua Osmanski; Robert Winter 003; Arvind Ramaprasan; Ann Kelley; Mary Shea; Saranrat Wittayanukorn; et al. (J. Am. Medical Informatics Assoc., 2024)