Health Literacy, Education Levels, and Patient Portal Usage During Hospitalizations. - Sharon E. Davis; Chandra Y. Osborn; Sunil Kripalani; Kathryn Goggins; Gretchen Purcell Jackson (AMIA, 2015)

Adoption of Secure Messaging in a Patient Portal across Pediatric Specialties. - Mary Masterman; Robert M. Cronin; Sharon E. Davis; Jared A. Shenson; Gretchen Purcell Jackson (AMIA, 2016)

Use of a Patient Portal During Hospital Admissions to Surgical Services. - Jamie R. Robinson; Sharon E. Davis; Robert M. Cronin; Gretchen Purcell Jackson (AMIA, 2016)

Calibration Drift of Clinical Prediction Models Across Modeling Methods. - Sharon E. Davis; Thomas A. Lasko; Guanhua Chen 002; Michael E. Matheny (CRI, 2016)

Using a Multilayer Self-Organizing Map for Risk Prediction in Hepatorenal Syndrome. - Jejo D. Koola; Sharon E. Davis; Samuel B. Ho; Michael E. Matheny (CRI, 2016)

Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality. - Sharon E. Davis; Thomas A. Lasko; Guanhua Chen 002; Michael E. Matheny (AMIA, 2017)

Machine Learning Models to Predict Readmission for Patients with Cirrhosis. - Jejo D. Koola; Aize Cao; Guanhua Chen 002; Amy Perkins; Samuel B. Ho; Sharon E. Davis; Michael E. Matheny (AMIA, 2017)

Long-term Patterns of Patient Portal Use for Pediatric Patients at an Academic Medical Center. - Robert M. Cronin; Sharon E. Davis; Ellen Yan; Gretchen P. Jackson; Bryan D. Steitz (Appl. Clin. Inform., 2017)

Calibration drift in regression and machine learning models for acute kidney injury. - Sharon E. Davis; Thomas A. Lasko; Guanhua Chen 002; Edward D. Siew; Michael E. Matheny (J. Am. Medical Informatics Assoc., 2017)

Developing a Testing Procedure to Select Model Updating Methods. - Sharon E. Davis; Robert A. Greevy Jr.; Michael E. Matheny (AMIA, 2018)

Development of an automated phenotyping algorithm for hepatorenal syndrome. - Jejo D. Koola; Sharon E. Davis; Omar Al-Nimri; Sharidan K. Parr; Daniel Fabbri; Bradley A. Malin; Samuel B. Ho; Michael E. Matheny (J. Biomed. Informatics, 2018)

Comparison of Prediction Model Performance Updating Protocols: Using a Data-Driven Testing Procedure to Guide Updating. - Sharon E. Davis; Robert A. Greevy Jr.; Thomas A. Lasko; Colin G. Walsh; Michael E. Matheny (AMIA, 2019)

A nonparametric updating method to correct clinical prediction model drift. - Sharon E. Davis; Robert A. Greevy Jr.; Christopher Fonnesbeck; Thomas A. Lasko; Colin G. Walsh; Michael E. Matheny (J. Am. Medical Informatics Assoc., 2019)

A Surveillance Framework for Monitoring and Updating Clinical Prediction Models. - Sharon E. Davis; Robert A. Greevy Jr.; Thomas A. Lasko; Colin G. Walsh; Michael E. Matheny (AMIA, 2020)

Detection of calibration drift in clinical prediction models to inform model updating. - Sharon E. Davis; Robert A. Greevy Jr.; Thomas A. Lasko; Colin G. Walsh; Michael E. Matheny (J. Biomed. Informatics, 2020)

Disparities in Coded and Imputed Post-Traumatic Stress Disorder and Self-Harm Among US Veterans. - Sharon E. Davis; Praveen Kumar; Nicolas R. Lauve; Sharidan K. Parr; Daniel Park; Michael E. Matheny; Gerardo Villarreal; George Uhl; Yiliang Zhu 001; Mauricio Tohen; Douglas J. Perkins; Christophe G. Lambert (AMIA, 2021)

A Framework for Generating Synthetic Clinical Datasets with Learning Effects to Support Methods Development and Validation. - Sharon E. Davis; Henry Ssemaganda; Jejo Koola; Jialin Mao; Dax M. Westerman; Theodore Speroff; Usha Govindarajulu; Craig Ramsay; Lucila Ohno-Machado; Frederic S. Resnic; Michael E. Matheny (AMIA, 2022)

A Framework for Detecting Medical Device Safety Signals Confounded by Learning Effects Using Machine Learning. - Jejo D. Koola; Jialin Mao; Sharon E. Davis; Henry Ssemaganda; Dax M. Westerman; Lucila Ohno-Machado; Frederic S. Resnic; Michael E. Matheny (AMIA, 2022)

Disentangling and Characterizing Device Safety Signals and Learning Effects. - Henry Ssemaganda; Frederic S. Resnic; Sharon E. Davis; Usha Govindarajulu; Jejo Koola; Jialin Mao; Dax M. Westerman; Theodore Speroff; Craig Ramsay; Art Sedrakyan; Lucila Ohno-Machado; Michael E. Matheny (AMIA, 2022)

Open questions and research gaps for monitoring and updating AI-enabled tools in clinical settings. - Sharon E. Davis; Colin G. Walsh; Michael E. Matheny (Frontiers Digit. Health, 2022)

A framework for understanding label leakage in machine learning for health care. - Sharon E. Davis; Michael E. Matheny; Suresh Balu; Mark P. Sendak (J. Am. Medical Informatics Assoc., 2023)

Sustainable deployment of clinical prediction tools - a 360° approach to model maintenance. - Sharon E. Davis; Peter J. Embí; Michael E. Matheny (J. Am. Medical Informatics Assoc., 2024)

Emerging algorithmic bias: fairness drift as the next dimension of model maintenance and sustainability. - Sharon E. Davis; Chad Dorn; Daniel J. Park; Michael E. Matheny (J. Am. Medical Informatics Assoc., 2025)

A machine learning framework to adjust for learning effects in medical device safety evaluation. - Jejo D. Koola; Karthik Ramesh; Jialin Mao; Minyoung Ahn; Sharon E. Davis; Usha Govindarajulu; Amy Perkins; Dax M. Westerman; Henry Ssemaganda; Theodore Speroff; Lucila Ohno-Machado; Craig Ramsay; et al. (J. Am. Medical Informatics Assoc., 2025)

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning. - Praveen Kumar; Fariha Moomtaheen; Scott A. Malec; Jeremy J. Yang; Cristian Bologa; Kristan Alexander Schneider; Yiliang Zhu 001; Mauricio Tohen; Gerardo Villarreal; Douglas J. Perkins; Elliot M. Fielstein; Sharon E. Davis; et al. (IEEE J. Biomed. Health Informatics, 2025)