Generating pregnant patient biological profiles by deconvoluting clinical records with electronic health record foundation models. - David Seong; Samson Mataraso; Camilo Espinosa; Eloïse Berson; S. Momsen Reincke; Lei Xue; Chloe Kashiwagi; Yeasul Kim; Chi-Hung Shu; Philip Chung 005; Marc Ghanem; Feng Xie 004; et al. (Briefings Bioinform., 2024)

Large Language Model Capabilities in Perioperative Risk Prediction and Prognostication. - Philip Chung 005; Christine T. Fong; Andrew M. Walters; Nima Aghaeepour; Meliha Yetisgen; Vikas N. O'Reilly-Shah (CoRR, 2024)

Assessing the Limitations of Large Language Models in Clinical Fact Decomposition. - Monica Munnangi; Akshay Swaminathan; Jason Alan Fries; Jenelle A. Jindal; Sanjana Narayanan; Iván López; Lucia Tu; Philip Chung 005; Jesutofunmi A. Omiye; Mehr Kashyap; Nigam Shah (CoRR, 2024)

Mitigation of outcome conflation in predicting patient outcomes using electronic health records. - S. Momsen Reincke; Camilo Espinosa; Philip Chung 005; Tomin James; Eloïse Berson; Nima Aghaeepour (J. Am. Medical Informatics Assoc., 2025)

VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records. - Philip Chung 005; Akshay Swaminathan; Alex J. Goodell; Yeasul Kim; S. Momsen Reincke; Lichy Han; Ben Deverett; Mohammad Amin Sadeghi; Abdel-Badih Ariss; Marc Ghanem; David Seong; Andrew A. Lee; et al. (CoRR, 2025)

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)