Belligoli, P., Bitterman, D., Miller, T. (2025). Do They Really Know? Evaluating Large Language Models’ Ability to Reference and Cite Oncology Guidelines. In: Bellazzi, R., Juarez Herrero, J.M., Sacchi, L., Zupan, B. (eds) Artificial Intelligence in Medicine. AIME 2025. Lecture Notes in Computer Science(), vol 15735. Springer, Cham. https://doi.org/10.1007/978-3-031-95841-0_6 (Details)

Wunnava S, Miller TA, Nathan M, Bourgeois FT. FDA Approval of Cardiac Valve Devices Implanted in a National Cohort of Pediatric Patients, 2016-2022. JAMA Pediatr. Published online March 24, 2025. doi:10.1001/jamapediatrics.2025.0131 (Details)

Yanjun Gao, Skatje Myers, Shan Chen, Dmitriy Dligach, Timothy Miller, Danielle S Bitterman, Guanhua Chen, Anoop Mayampurath, Matthew M Churpek, Majid Afshar, Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability, JAMIA Open, Volume 8, Issue 1, February 2025, ooae154, https://doi.org/10.1093/jamiaopen/ooae154 (Details)

WonJin Yoon, Shan Chen, Yanjun Gao, Zhanzhan Zhao, Dmitriy Dligach, Danielle S Bitterman, Majid Afshar, Timothy Miller, LCD benchmark: long clinical document benchmark on mortality prediction for language models. Journal of the American Medical Informatics Association, 2024, ocae287, https://doi.org/10.1093/jamia/ocae287 (Details)

Weipeng Zhou, Timothy Miller. 2024. Generalizable clinical note section identification with large language models, JAMIA Open, Volume 7, Issue 3, October 2024, ooae075, https://doi.org/10.1093/jamiaopen/ooae075 (Details)