Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data. - Joseph Futoma; Mark P. Sendak; Blake Cameron; Katherine A. Heller (MLHC, 2016)

Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease. - Joseph Futoma; Mark P. Sendak; Blake Cameron; Katherine A. Heller (UAI, 2016)

An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection. - Joseph Futoma; Sanjay Hariharan; Katherine A. Heller; Mark P. Sendak; Nathan Brajer; Meredith Clement; Armando Bedoya; Cara O'Brien (MLHC, 2017)

Barriers to Achieving Economies of Scale in Analysis of EHR Data. - Mark P. Sendak; Suresh Balu; Kevin A. Schulman (Appl. Clin. Inform., 2017)

Translating, Implementing, Deploying, and Evaluating Clinical Interventions Using Machine Learning Based Predictive Models: Illustrative Case Studies. - Yindalon Aphinyanaphongs; Jonathan K. Wilt; Corey J. Chivers; Mark P. Sendak (AMIA, 2019)

"The human body is a black box": supporting clinical decision-making with deep learning. - Mark P. Sendak; Madeleine Clare Elish; Michael Gao; Joseph Futoma; William Ratliff; Marshall Nichols; Armando Bedoya; Suresh Balu; Cara O'Brien (FAT*, 2020)

Presenting machine learning model information to clinical end users with model facts labels. - Mark P. Sendak; Michael Gao; Nathan Brajer; Suresh Balu (npj Digit. Medicine, 2020)

Impact of diagnosis code grouping method on clinical prediction model performance: A multi-site retrospective observational study. - Aman Kansal; Michael Gao; Suresh Balu; Marshall Nichols; Kristin Corey; Sehj Kashyap; Mark P. Sendak (Int. J. Medical Informatics, 2021)

Looking for clinician involvement under the wrong lamp post: The need for collaboration measures. - Mark P. Sendak; Michael Gao; William Ratliff; Marshall Nichols; Armando Bedoya; Cara O'Brien; Suresh Balu (J. Am. Medical Informatics Assoc., 2021)

Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare. - Mark P. Sendak; Gaurav Sirdeshmukh; Timothy Ochoa; Hayley Premo; Linda Tang; Kira Niederhoffer; Sarah Reed; Kaivalya Deshpande; Emily Sterrett; Melissa Bauer; Laurie Snyder; Afreen Shariff; et al. (MLHC, 2022)

Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. - Jee Young Kim; William Boag; Freya Gulamali; Alifia Hasan; Henry David Jeffry Hogg; Mark Lifson; Deirdre K. Mulligan; Manesh Patel; Inioluwa Deborah Raji; Ajai Sehgal; Keo Shaw; Danny Tobey; et al. (FAccT, 2023)

Editorial: Surfacing best practices for AI software development and integration in healthcare. - Mark P. Sendak; David E. Vidal; Sylvia Trujillo; Karandeep Singh; Xiaoxuan Liu; Suresh Balu (Frontiers Digit. Health, 2023)

Accelerating health system innovation: principles and practices from the Duke Institute for Health Innovation. - Sahil Sandhu; Mark P. Sendak; William Ratliff; William Knechtle; William J. Fulkerson; Suresh Balu (Patterns, 2023)

Enabling collaborative governance of medical AI. - W. Nicholson Price; Mark P. Sendak; Suresh Balu; Karandeep Singh (Nat. Mac. Intell., 2023)

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)

Strengthening the use of artificial intelligence within healthcare delivery organizations: balancing regulatory compliance and patient safety. - Mark P. Sendak; Vincent X. Liu; Ashley Beecy; David E. Vidal; Keo Shaw; Mark Lifson; Danny Tobey; Alexandra Valladares; Brenna Loufek; Murtaza Mogri; Suresh Balu (J. Am. Medical Informatics Assoc., 2024)

The algorithm journey map: a tangible approach to implementing AI solutions in healthcare. - William Boag; Alifia Hasan; Jee Young Kim; Mike Revoir; Marshall Nichols; William Ratliff; Michael Gao; Shira Zilberstein; Zainab Samad; Zahra Hoodbhoy; Mushyada Ali; Nida Saddaf Khan; et al. (npj Digit. Medicine, 2024)

From pre-test and post-test probabilities to medical decision making. - Michelle Pistner Nixon; Farhani Momotaz; Claire Smith; Jeffrey S. Smith; Mark P. Sendak; Christopher Polage; Justin D. Silverman (BMC Medical Informatics Decis. Mak., 2024)

Regulation of artificial intelligence in healthcare: Clinical Laboratory Improvement Amendments (CLIA) as a model. - Brian R. Jackson; Mark P. Sendak; Anthony Solomonides; Suresh Balu; Dean F. Sittig (J. Am. Medical Informatics Assoc., 2025)

AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. - Shalmali Joshi; Iñigo Urteaga; Wouter A. C. van Amsterdam; George Hripcsak; Pierre A. Elias; Benjamin R. C. Amor; Noémie Elhadad; James C. Fackler; Mark P. Sendak; Jenna Wiens; Kaivalya Deshpande; Yoav Wald; et al. (J. Am. Medical Informatics Assoc., 2025)

Aligning AI principles and healthcare delivery organization best practices to navigate the shifting regulatory landscape. - Alifia Hasan; Noah Prizant; Jee Young Kim; Shreya Rao; David E. Vidal; Keo Shaw; Danny Tobey; Alexandra Valladares; Shira Zilberstein; Manesh Patel; Suresh Balu; Mark P. Sendak; et al. (npj Digit. Medicine, 2025)

Evaluating sepsis watch generalizability through multisite external validation of a sepsis machine learning model. - Bruno Valan; Anusha Prakash 003; William Ratliff; Michael Gao; Srikanth Muthya; Ajit Thomas; Jennifer L. Eaton; Matt Gardner 004; Marshall Nichols; Mike Revoir; Dustin Tart; Cara O'Brien; et al. (npj Digit. Medicine, 2025)

Bridging Prediction and Intervention Problems in Social Systems. - Lydia T. Liu; Inioluwa Deborah Raji; Angela Zhou; Luke Guerdan; Jessica Hullman; Daniel Malinsky; Bryan Wilder; Simone Zhang; Hammaad Adam; Amanda Coston; Benjamin Laufer; Ezinne Nwankwo; et al. (CoRR, 2025)