Considerations for addressing bias in artificial intelligence for health equity. - Michael D. Abràmoff; Michelle E. Tarver; Nilsa Loyo-Berrios; Sylvia Trujillo; Danton Char; Ziad Obermeyer; Malvina B. Eydelman; William H. Maisel (npj Digit. Medicine, 2023)

A framework to identify ethical concerns with ML-guided care workflows: a case study of mortality prediction to guide advance care planning. - Diana Cagliero; Natalie Deuitch; Nigam Shah; Chris Feudtner; Danton Char (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)

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks. - Suhana Bedi; Hejie Cui; Miguel Fuentes; Alyssa Unell; Michael Wornow; Juan M. Banda; Nikesh Kotecha; Timothy Keyes; Yifan Mai 001; Mert Oez; Hao Qiu; Shrey Jain; et al. (CoRR, 2025)