FIBERNET 2.0: An automatic neural network based tool for clustering white matter fibers in the brain. - Vikash Gupta; Sophia I. Thomopoulos; Conor K. Corbin; Faisal Rashid; Paul M. Thompson (ISBI, 2018)

Associations Between Maternal Depression and Infant Fronto-Limbic Connectivity. - Emily L. Dennis; Ananya Singh; Conor K. Corbin; Neda Jahanshad; Tiffany C. Ho; Lucy S. King; Lauren R. Borchers; Kathryn L. Humphreys; Paul M. Thompson; Ian H. Gotlib (ISBI, 2019)

Context is Key: Using the Audit Log to Capture Contextual Factors Affecting Stroke Care Processes. - Morteza Noshad; Christian Rose; Robert Thombley; Jonathan Chiang; Conor K. Corbin; Minh Nguyen; Vincent X. Liu; Julia Adler-Milstein; Jonathan H. Chen (AMIA, 2020)

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data. - Ethan Steinberg; Kenneth Jung; Jason A. Fries; Conor K. Corbin; Stephen R. Pfohl; Nigam H. Shah (CoRR, 2020)

Estimating the efficacy of symptom-based screening for COVID-19. - Alison Callahan; Ethan Steinberg; Jason A. Fries; Saurabh Gombar; Birju S. Patel; Conor K. Corbin; Nigam H. Shah (npj Digit. Medicine, 2020)

A Retrospective Analysis of Machine Learning Driven Antibiotic Selection in the Emergency Department. - Conor K. Corbin; Arhana Chattopadhyah; Lillian Sung; Amy Chang; Stan Deresinski; Jonathan H. Chen (AMIA, 2021)

Predicting Level of Care for Emergency Hospital Admissions to Optimize Triage. - Minh Nguyen; Nicolai P. Ostberg; Conor K. Corbin; Tiffany Eulalio; Gautam Machiraju; Ben J. Marafino; Michael T. M. Baiocchi; Christian Rose; Jonathan H. Chen (AMIA, 2021)

Developing machine learning models to personalize care levels among emergency room patients for hospital admission. - Minh Nguyen; Conor K. Corbin; Tiffany Eulalio; Nicolai P. Ostberg; Gautam Machiraju; Ben J. Marafino; Michael T. M. Baiocchi; Christian Rose; Jonathan H. Chen (J. Am. Medical Informatics Assoc., 2021)

Language models are an effective representation learning technique for electronic health record data. - Ethan Steinberg; Kenneth Jung; Jason A. Fries; Conor K. Corbin; Stephen R. Pfohl; Nigam H. Shah (J. Biomed. Informatics, 2021)

How to Avoid Incorrect Clinical Machine Learning Model Performance Estimates When Class Labels Are Only Partially Observed. - Conor K. Corbin; Michael T. M. Baiocchi; Jonathan H. Chen (AMIA, 2022)

Avoiding Biased Clinical Machine Learning Model Performance Estimates in the Presence of Label Selection. - Conor K. Corbin; Michael T. M. Baiocchi; Jonathan H. Chen (CoRR, 2022)

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record. - Conor K. Corbin; Rob Maclay; Aakash Acharya; Sreedevi Mony; Soumya Punnathanam; Rahul Thapa; Nikesh Kotecha; Nigam H. Shah; Jonathan H. Chen (J. Am. Medical Informatics Assoc., 2023)

Standing on FURM ground - A framework for evaluating Fair, Useful, and Reliable AI Models in healthcare systems. - Alison Callahan; Duncan C. McElfresh; Juan M. Banda; Gabrielle Bunney; Danton Char; Jonathan H. Chen; Conor K. Corbin; Debadutta Dash; Norman L. Downing; Sneha S. Jain; Nikesh Kotecha; Jonathan Masterson; et al. (CoRR, 2024)

Monitoring strategies for continuous evaluation of deployed clinical prediction models. - Grace Y. E. Kim; Conor K. Corbin; François Grolleau; Michael T. M. Baiocchi; Jonathan H. Chen (J. Biomed. Informatics, 2025)