Machine learning in the social and health sciences. - Anja K. Leist; Matthias Klee; Jung Hyun Kim; David H. Rehkopf; Stéphane P. A. Bordas; Graciela Muniz-Terrera; Sara Wade (CoRR, 2021)

Potential for allocative harm in an environmental justice data tool. - Benjamin Q. Huynh; Elizabeth T. Chin; Allison Koenecke; Derek Ouyang; Daniel E. Ho; Mathew V. Kiang; David H. Rehkopf (CoRR, 2023)

Mitigating allocative tradeoffs and harms in an environmental justice data tool. - Benjamin Q. Huynh; Elizabeth T. Chin; Allison Koenecke; Derek Ouyang; Daniel E. Ho; Mathew V. Kiang; David H. Rehkopf (Nat. Mac. Intell., 2024)

Incorporating area-level social drivers of health in predictive algorithms using electronic health record data. - Agata Foryciarz; Nicole Gladish; David H. Rehkopf; Sherri Rose (J. Am. Medical Informatics Assoc., 2025)

Linking national primary care electronic health records to individual records from the U.S. Census Bureau's American Community Survey: evaluating the likelihood of linkage based on patient health. - Aubrey Limburg; Nicole Gladish; David H. Rehkopf; Robert L. Phillips; Victoria Udalova (J. Am. Medical Informatics Assoc., 2025)