Extracting Relations between Radiotherapy Treatment Details. - Danielle S. Bitterman; Timothy Miller 002; David Harris 004; Chen Lin 002; Sean Finan; Jeremy L. Warner; Raymond H. Mak; Guergana Savova (ClinicalNLP@EMNLP, 2020)

Deep-learning system to improve the quality and efficiency of volumetric heart segmentation for breast cancer. - Roman Zeleznik; Jakob Weiss; Jana Taron; Christian V. Guthier; Danielle S. Bitterman; Cindy Hancox; Benjamin H. Kann; Daniel W. Kim; Rinaa S. Punglia; Jeremy Bredfeldt; Borek Foldyna; Parastou Eslami; et al. (npj Digit. Medicine, 2021)

Classifying unstructured electronic consult messages to understand primary care physician specialty information needs. - Xiyu Ding; Michael L. Barnett; Ateev Mehrotra; Delphine S. Tuot; Danielle S. Bitterman; Timothy A. Miller (J. Am. Medical Informatics Assoc., 2022)

Measuring Pointwise mathcalV-Usable Information In-Context-ly. - Sheng Lu; Shan Chen 004; Yingya Li; Danielle S. Bitterman; Guergana Savova; Iryna Gurevych (EMNLP (Findings), 2023)

Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy. - Shan Chen 004; Marco Guevara; Nicolas Ramirez; Arpi Murray; Jeremy L. Warner; Hugo J. W. L. Aerts; Timothy A. Miller; Guergana K. Savova; Raymond H. Mak; Danielle S. Bitterman (CoRR, 2023)

Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification. - Shan Chen 004; Yingya Li; Sheng Lu; Hoang Van; Hugo J. W. L. Aerts; Guergana K. Savova; Danielle S. Bitterman (CoRR, 2023)

Large Language Models to Identify Social Determinants of Health in Electronic Health Records. - Marco Guevara; Shan Chen 004; Spencer Thomas; Tafadzwa L. Chaunzwa; Idalid Franco; Benjamin H. Kann; Shalini Moningi; Jack M. Qian; Madeleine Goldstein; Susan Harper; Hugo J. W. L. Aerts; Guergana K. Savova; et al. (CoRR, 2023)

Considerations for health care institutions training large language models on electronic health records. - Weipeng Zhou; Danielle S. Bitterman; Majid Afshar; Timothy A. Miller (CoRR, 2023)

Measuring Pointwise $ mathcal{V}$-Usable Information In-Context-ly. - Sheng Lu; Shan Chen 004; Yingya Li; Danielle S. Bitterman; Guergana Savova; Iryna Gurevych (CoRR, 2023)

The impact of using an AI chatbot to respond to patient messages. - Shan Chen 004; Marco Guevara; Shalini Moningi; Frank Hoebers; Hesham Elhalawani; Benjamin H. Kann; Fallon E. Chipidza; Jonathan Leeman; Hugo J. W. L. Aerts; Timothy A. Miller; Guergana K. Savova; Raymond H. Mak; et al. (CoRR, 2023)

Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks. - Jack Gallifant; Shan Chen 004; Pedro Moreira; Nikolaj Munch; Mingye Gao; Jackson Pond; Leo Anthony Celi; Hugo J. W. L. Aerts; Thomas Hartvigsen; Danielle S. Bitterman (EMNLP (Findings), 2024)

When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications? - Yanjun Gao; Skatje Myers; Shan Chen 004; Dmitriy Dligach; Timothy A. Miller; Danielle S. Bitterman; Matthew M. Churpek; Majid Afshar (EMNLP (Findings), 2024)

Seeing Beyond Borders: Evaluating LLMs in Multilingual Ophthalmological Question Answering. - David S. Restrepo; Luis Filipe Nakayama; Robyn Gayle Dychiao; Chenwei Wu 006; Liam G. McCoy; Jose Carlo Artiaga; Marisa Cobanaj; João Matos; Jack Gallifant; Danielle S. Bitterman; Vincenz Ferrer; Yindalon Aphinyanaphongs; et al. (ICHI, 2024)

Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias. - Shan Chen 004; Jack Gallifant; Mingye Gao; Pedro Moreira; Nikolaj Munch; Ajay Muthukkumar; Arvind Rajan; Jaya Kolluri; Amelia Fiske; Janna Hastings; Hugo J. W. L. Aerts; Brian Anthony; et al. (NeurIPS, 2024)

Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data. - Shan Chen 004; Jack Gallifant; Marco Guevara; Yanjun Gao; Majid Afshar; Timothy Miller 002; Dmitriy Dligach; Danielle S. Bitterman (CoRR, 2024)

Seeds of Stereotypes: A Large-Scale Textual Analysis of Race and Gender Associations with Diseases in Online Sources. - Lasse Hyldig Hansen; Nikolaj Andersen; Jack Gallifant; Liam G. McCoy; James K. Stone; Nura Izath; Marcela Aguirre-Jerez; Danielle S. Bitterman; Judy Gichoya; Leo Anthony Celi (CoRR, 2024)

Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine. - Rui Yang 016; Yilin Ning; Emilia Keppo; Mingxuan Liu; Chuan Hong; Danielle S. Bitterman; Jasmine Chiat Ling Ong; Daniel Shu Wei Ting; Nan Liu 003 (CoRR, 2024)

AIPatient: Simulating Patients with EHRs and LLM Powered Agentic Workflow. - Huizi Yu; Jiayan Zhou; Lingyao Li; Shan Chen 004; Jack Gallifant; Anye Shi; Xiang Li; Wenyue Hua; Mingyu Jin; Guang Chen; Yang Zhou; Zhao Li; et al. (CoRR, 2024)

Safety challenges of AI in medicine. - Xiaoye Wang; Nicole Xi Zhang; Hongyu He; Trang Nguyen; Kun-Hsing Yu; Hao Deng; Cynthia Brandt; Danielle S. Bitterman; Ling Pan; Ching-Yu Cheng; James Zou; Dianbo Liu (CoRR, 2024)

Wait, but Tylenol is Acetaminophen... Investigating and Improving Language Models' Ability to Resist Requests for Misinformation. - Shan Chen 004; Mingye Gao; Kuleen Sasse; Thomas Hartvigsen; Brian Anthony; Lizhou Fan; Hugo J. W. L. Aerts; Jack Gallifant; Danielle S. Bitterman (CoRR, 2024)

Mapping Bias in Vision Language Models: Signposts, Pitfalls, and the Road Ahead. - Kuleen Sasse; Shan Chen 004; Jackson Pond; Danielle S. Bitterman; John D. Osborne (CoRR, 2024)

Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability. - Yanjun Gao; Skatje Myers; Shan Chen 004; Dmitriy Dligach; Timothy A. Miller; Danielle S. Bitterman; Guanhua Chen; Anoop M. Mayampurath; Matthew M. Churpek; Majid Afshar (CoRR, 2024)

ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction? - Canyu Chen; Jian Yu; Shan Chen 004; Che Liu; Zhongwei Wan; Danielle S. Bitterman; Fei Wang; Kai Shu (CoRR, 2024)

The use of large language models to enhance cancer clinical trial educational materials. - Mingye Gao; Aman Varshney; Shan Chen 004; Vikram Goddla; Jack Gallifant; Patrick Doyle; Claire Novack; Maeve Dillon-Martin; Teresia Perkins; Xinrong Correia; Erik P. Duhaime; Howard Isenstein; et al. (CoRR, 2024)

Evaluating the ChatGPT family of models for biomedical reasoning and classification. - Shan Chen 004; Yingya Li; Sheng Lu; Hoang Van; Hugo J. W. L. Aerts; Guergana K. Savova; Danielle S. Bitterman (J. Am. Medical Informatics Assoc., 2024)

Ethical debates amidst flawed healthcare artificial intelligence metrics. - Jack Gallifant; Danielle S. Bitterman; Leo Anthony Celi; Judy W. Gichoya; João Matos; Liam G. McCoy; Robin L. Pierce (npj Digit. Medicine, 2024)

Large language models to identify social determinants of health in electronic health records. - Marco Guevara; Shan Chen 004; Spencer Thomas; Tafadzwa L. Chaunzwa; Idalid Franco; Benjamin H. Kann; Shalini Moningi; Jack M. Qian; Madeleine Goldstein; Susan Harper; Hugo J. W. L. Aerts; Paul J. Catalano; et al. (npj Digit. Medicine, 2024)

Multi-OphthaLingua: A Multilingual Benchmark for Assessing and Debiasing LLM Ophthalmological QA in LMICs. - David S. Restrepo; Chenwei Wu 006; Zhengxu Tang; Zitao Shuai; Thao Nguyen Minh Phan; Jun-En Ding; Cong-Tinh Dao; Jack Gallifant; Robyn Gayle Dychiao; Jose Carlo Artiaga; André Hiroshi Bando; Carolina Pelegrini Barbosa Gracitelli; et al. (AAAI, 2025)

Do They Really Know? Evaluating Large Language Models' Ability to Reference and Cite Oncology Guidelines. - Pietro Belligoli; Danielle S. Bitterman; Timothy A. Miller (AIME (2), 2025)

WorldMedQA-V: a multilingual, multimodal medical examination dataset for multimodal language models evaluation. - João Matos; Shan Chen 004; Siena Placino; Yingya Li; Juan Carlos Climent Pardo; Daphna Idan; Takeshi Tohyama; David S. Restrepo; Luis Filipe Nakayama; Jose M. M. Pascual-Leone; Guergana K. Savova; Hugo J. W. L. Aerts; et al. (NAACL (Findings), 2025)

Collaborative large language models for automated data extraction in living systematic reviews. - Muhammad Ali Khan; Umair Ayub; Syed Arsalan Ahmed Naqvi; Kaneez Zahra Rubab Khakwani; Zaryab bin Riaz Sipra; Ammad Raina; Sihan Zhou; Huan He; Amir Saeidi; Bashar Hasan; Robert Bryan Rumble; Danielle S. Bitterman; et al. (J. Am. Medical Informatics Assoc., 2025)

LCD benchmark: long clinical document benchmark on mortality prediction for language models. - Wonjin Yoon; Shan Chen 004; Yanjun Gao; Zhanzhan Zhao; Dmitriy Dligach; Danielle S. Bitterman; Majid Afshar; Timothy A. Miller (J. Am. Medical Informatics Assoc., 2025)

Preventing unrestricted and unmonitored AI experimentation in healthcare through transparency and accountability. - Donnella S. Comeau; Danielle S. Bitterman; Leo Anthony Celi (npj Digit. Medicine, 2025)

Regulatory Science Innovation for Generative AI and Large Language Models in Health and Medicine: A Global Call for Action. - Jasmine Chiat Ling Ong; Yilin Ning; Mingxuan Liu; Yian Ma; Zhao Liang; Kuldev Singh; Robert T. Chang; Silke Vogel; John CW Lim; Iris Siu Kwan Tan; Oscar Freyer; Stephen Gilbert; et al. (CoRR, 2025)

Sparse Autoencoder Features for Classifications and Transferability. - Jack Gallifant; Shan Chen 004; Kuleen Sasse; Hugo J. W. L. Aerts; Thomas Hartvigsen; Danielle S. Bitterman (CoRR, 2025)

MedBrowseComp: Benchmarking Medical Deep Research and Computer Use. - Shan Chen 004; Pedro Moreira; Yuxin Xiao; Sam Schmidgall; Jeremy L. Warner; Hugo J. W. L. Aerts; Thomas Hartvigsen; Jack Gallifant; Danielle S. Bitterman (CoRR, 2025)

When Models Reason in Your Language: Controlling Thinking Trace Language Comes at the Cost of Accuracy. - Jirui Qi; Shan Chen; Zidi Xiong; Raquel Fernández; Danielle S. Bitterman; Arianna Bisazza (CoRR, 2025)

KScope: A Framework for Characterizing the Knowledge Status of Language Models. - Yuxin Xiao; Shan Chen 004; Jack Gallifant; Danielle S. Bitterman; Thomas Hartvigsen; Marzyeh Ghassemi (CoRR, 2025)

Foundation Artificial Intelligence Models for Health Recognition Using Face Photographs (FAHR-Face). - Fridolin Haugg; Grace Lee; John He; Leonard Nürnberg; Dennis Bontempi; Danielle S. Bitterman; Paul J. Catalano; Vasco Prudente; Dmitrii Glubokov; Andrew Warrington; Suraj Pai; Dirk De Ruysscher; et al. (CoRR, 2025)