Comparison of Operating Characteristics of Commonly Used Sample Size Re-Estimation Procedures in a Two-Stage Design. - Sandeep Menon; Joseph Massaro; Michael J. Pencina; Jerry Lewis; Yong Cheng Wang (Commun. Stat. Simul. Comput., 2013)

A Systematic Review of Using Electronic Heath Records to Predict Clinical Events: Assessment of Opportunities and Challenges. - Benjamin Alan Goldstein; Ann Marie Navar; Michael J. Pencina; John P. A. Ioannidis (CRI, 2016)

Developing a framework for a comprehensive data sharing program. - Asba Tasneem; Karen Chiswell; Brian J. McCourt; Matt Gross; Eric D. Peterson; Michael J. Pencina (AMIA, 2017)

Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review. - Benjamin Alan Goldstein; Ann Marie Navar; Michael J. Pencina; John P. A. Ioannidis (J. Am. Medical Informatics Assoc., 2017)

Predicting mortality over different time horizons: which data elements are needed? - Benjamin Alan Goldstein; Michael J. Pencina; Maria E. Montez-Rath; Wolfgang C. Winkelmayer (J. Am. Medical Informatics Assoc., 2017)

Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus. - Susan E. Spratt; Katherine Pereira; Bradi B. Granger; Bryan C. Batch; Matthew Phelan; Michael J. Pencina; Marie Lynn Miranda; L. Ebony Boulware; Joseph E. Lucas; Charlotte L. Nelson; Benjamin Neely; Benjamin Alan Goldstein; et al. (J. Am. Medical Informatics Assoc., 2017)

The Duke Health Data Science Internship Program: Integrating the Educational Mission into Real-World Research. - Shelley A. Rusincovitch; Lisa Wruck; Ricardo Henao; Larisa Rodgers; Allison Dunning; Peter Merrill; Hillary Mulder; Robert Overton; Matthew Phelan; Erich Huang; Lawrence Carin; Michael J. Pencina (AMIA, 2018)

Microsimulation model to predict incremental value of biomarkers added to prognostic models. - Karol M. Pencina; Ralph B. D'Agostino; Ramachandran S. Vasan; Michael J. Pencina (J. Am. Medical Informatics Assoc., 2018)

Informatics-Enabled Learning Health Systems: Strategies for Success from Four Academic Medical Centers. - Eric G. Poon; Charles P. Friedman; Philip R. O. Payne; Michael J. Pencina; Kevin B. Johnson (AMIA, 2019)

An outcome model approach to transporting a randomized controlled trial results to a target population. - Benjamin Alan Goldstein; Matthew Phelan; Neha J. Pagidipati; Rury R. Holman; Michael J. Pencina; Elizabeth A. Stuart (J. Am. Medical Informatics Assoc., 2019)

Survival Analysis meets Counterfactual Inference. - Paidamoyo Chapfuwa; Serge Assaad; Shuxi Zeng; Michael J. Pencina; Lawrence Carin; Ricardo Henao (CoRR, 2020)

The Project Baseline Health Study: a step towards a broader mission to map human health. - Kristine Arges; Themistocles L. Assimes; Vikram Bajaj; Suresh Balu; Mustafa R. Bashir; Laura Beskow; Rosalia Blanco; Robert M. Califf; Paul Campbell; Larry Carin; Victoria Christian; Scott Cousins; et al. (npj Digit. Medicine, 2020)

Understanding Algorithmic Bias in Clinical Prediction Models. - Mengying Yan; Michael J. Pencina; Benjamin Alan Goldstein (AMIA, 2021)

Enabling counterfactual survival analysis with balanced representations. - Paidamoyo Chapfuwa; Serge Assaad; Shuxi Zeng; Michael J. Pencina; Lawrence Carin; Ricardo Henao (CHIL, 2021)

A framework for the oversight and local deployment of safe and high-quality prediction models. - Armando Bedoya; Nicoleta J. Economou-Zavlanos; Benjamin Alan Goldstein; Allison Young; John Eric Jelovsek; Cara O'Brien; Amanda B. Parrish; Scott Elengold; Kay Lytle; Suresh Balu; Erich Huang; Eric G. Poon; et al. (J. Am. Medical Informatics Assoc., 2022)

Observability and its impact on differential bias for clinical prediction models. - Mengying Yan; Michael J. Pencina; L. Ebony Boulware; Benjamin Alan Goldstein (J. Am. Medical Informatics Assoc., 2022)

All models are local: time to replace external validation with recurrent local validation. - Alexey Youssef; Michael J. Pencina; Anshul Thakur; Tingting Zhu 001; David A. Clifton; Nigam H. Shah (CoRR, 2023)

Improving Event Time Prediction by Learning to Partition the Event Time Space. - Jimmy Hickey; Ricardo Henao; Daniel Wojdyla; Michael J. Pencina; Matthew M. Engelhard (CoRR, 2023)

Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions. - Shauna M. Overgaard; Megan G. Graham; Tracey Brereton; Michael J. Pencina; John D. Halamka; David E. Vidal; Nicoleta J. Economou-Zavlanos (npj Digit. Medicine, 2023)

Calibration and Uncertainty in Neural Time-to-Event Modeling. - Paidamoyo Chapfuwa; Chenyang Tao; Chunyuan Li; Irfan Khan; Karen Chandross; Michael J. Pencina; Lawrence Carin; Ricardo Henao (IEEE Trans. Neural Networks Learn. Syst., 2023)

Semi-supervised calibration of noisy event risk (SCANER) with electronic health records. - Chuan Hong; Liang Liang; Qianyu Yuan; Kelly Cho; Katherine P. Liao; Michael J. Pencina; David C. Christiani; Tianxi Cai (J. Biomed. Informatics, 2023)

Adaptive Discretization for Event PredicTion (ADEPT). - Jimmy Hickey; Ricardo Henao; Daniel Wojdyla; Michael J. Pencina; Matthew Engelhard (AISTATS, 2024)

Distributionally Robust Clustered Federated Learning: A Case Study in Healthcare. - Xenia Konti; Hans Riess; Manos Giannopoulos; Yi Shen 011; Michael J. Pencina; Nicoleta J. Economou-Zavlanos; Michael M. Zavlanos (CDC, 2024)

Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance. - Chuan Hong; Molei Liu; Daniel Wojdyla; Jimmy Hickey; Michael J. Pencina; Ricardo Henao (J. Biomed. Informatics, 2024)

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare. - Nicoleta J. Economou-Zavlanos; Sophia Bessias; Michael P. Cary; Armando Bedoya; Benjamin Goldstein 001; John Eric Jelovsek; Cara O'Brien; Nancy Walden; Matthew Elmore; Amanda B. Parrish; Scott Elengold; Kay S. Lytle; et al. (J. Am. Medical Informatics Assoc., 2024)

Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models. - Matthew Engelhard; Daniel Wojdyla; Haoyuan Wang; Michael J. Pencina; Ricardo Henao (Artif. Intell. Medicine, 2025)

Application of unified health large language model evaluation framework to In-Basket message replies: bridging qualitative and quantitative assessments. - Chuan Hong; Anand Chowdhury; Anthony D. Sorrentino; Haoyuan Wang; Monica Agrawal; Armando Bedoya; Sophia Bessias; Nicoleta J. Economou-Zavlanos; Ian Wong; Christian Pean; Fan Li; Kathryn I. Pollak; et al. (J. Am. Medical Informatics Assoc., 2025)

An evaluation framework for ambient digital scribing tools in clinical applications. - Haoyuan Wang; Rui Yang; Mahmoud Alwakeel; Ankit Kayastha; Anand Chowdhury; Joshua M. Biro; Anthony D. Sorrentino; Jessica L. Handley; Sarah Hantzmon; Sophia Bessias; Nicoleta J. Economou-Zavlanos; Armando Bedoya; et al. (npj Digit. Medicine, 2025)

Enabling Inclusive Systematic Reviews: Incorporating Preprint Articles with Large Language Model-Driven Evaluations. - Rui Yang 016; Jiayi Tong; Haoyuan Wang; Hui Huang; Ziyang Hu; Peiyu Li; Nan Liu 003; Christopher J. Lindsell; Michael J. Pencina; Yong Chen 016; Chuan Hong (CoRR, 2025)

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport. - Pengxi Liu; Yi Shen 011; Matthew M. Engelhard; Benjamin Alan Goldstein; Michael J. Pencina; Nicoleta J. Economou-Zavlanos; Michael M. Zavlanos (CoRR, 2025)