Danielle S. Bitterman

According to our database, Danielle S. Bitterman authored at least 39 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Christian V. Guthier, Benjamin H. Kann, Vadim N. Gladyshev, Hugo J. W. L. Aerts, Raymond H. Mak

CoRR, June, 2025

KScope: A Framework for Characterizing the Knowledge Status of Language Models.

Yuxin Xiao, Shan Chen, Jack Gallifant, Danielle S. Bitterman, Thomas Hartvigsen, Marzyeh Ghassemi

CoRR, June, 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, May, 2025

MedBrowseComp: Benchmarking Medical Deep Research and Computer Use.

Shan Chen, Pedro Moreira, Yuxin Xiao, Sam Schmidgall, Jeremy L. Warner, Hugo J. W. L. Aerts, Thomas Hartvigsen, Jack Gallifant, Danielle S. Bitterman

CoRR, May, 2025

Sparse Autoencoder Features for Classifications and Transferability.

Jack Gallifant, Shan Chen, Kuleen Sasse, Hugo J. W. L. Aerts, Thomas Hartvigsen, Danielle S. Bitterman

CoRR, February, 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, Danielle S. Bitterman, Xiaoxuan Liu, Alastair K. Denniston, Nan Liu

CoRR, February, 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

LCD benchmark: long clinical document benchmark on mortality prediction for language models.

Wonjin Yoon, Shan Chen, Yanjun Gao, Zhanzhan Zhao, Dmitriy Dligach, Danielle S. Bitterman, Majid Afshar, Timothy A. Miller

J. Am. Medical Informatics Assoc., 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, Jeremy L. Warner, Jia Zou, Amye J. Tevaarwerk, Konstantinos Leventakos, Kenneth L. Kehl, Jeanne M. Palmer, Mohammad Hassan Murad, Chitta Baral, Irbaz Bin Riaz

J. Am. Medical Informatics Assoc., 2025

WorldMedQA-V: a multilingual, multimodal medical examination dataset for multimodal language models evaluation.

João Matos, Shan Chen, 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, Leo Anthony Celi, An-Kwok Ian Wong, Danielle S. Bitterman, Jack Gallifant

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Do They Really Know? Evaluating Large Language Models' Ability to Reference and Cite Oncology Guidelines.

Pietro Belligoli, Danielle S. Bitterman, Timothy A. Miller

Proceedings of the Artificial Intelligence in Medicine - 23rd International Conference, 2025

Multi-OphthaLingua: A Multilingual Benchmark for Assessing and Debiasing LLM Ophthalmological QA in LMICs.

David S. Restrepo, Chenwei Wu, 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, Vincenz Ferrer, Leo Anthony Celi, Danielle S. Bitterman, Michael G. Morley, Luis Filipe Nakayama

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Large language models to identify social determinants of health in electronic health records.

Marco Guevara, Shan Chen, 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, Guergana K. Savova, Raymond H. Mak, Danielle S. Bitterman

npj Digit. Medicine, 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

Evaluating the ChatGPT family of models for biomedical reasoning and classification.

Shan Chen, Yingya Li, Sheng Lu, Hoang Van, Hugo J. W. L. Aerts, Guergana K. Savova, Danielle S. Bitterman

J. Am. Medical Informatics Assoc., 2024

The use of large language models to enhance cancer clinical trial educational materials.

Mingye Gao, Aman Varshney, Shan Chen, Vikram Goddla, Jack Gallifant, Patrick Doyle, Claire Novack, Maeve Dillon-Martin, Teresia Perkins, Xinrong Correia, Erik P. Duhaime, Howard Isenstein, Elad Sharon, Lisa Soleymani Lehmann, David E. Kozono, Brian Anthony, Dmitriy Dligach, Danielle S. Bitterman

CoRR, 2024

ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?

Canyu Chen, Jian Yu, Shan Chen, Che Liu, Zhongwei Wan, Danielle S. Bitterman, Fei Wang, Kai Shu

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, Dmitriy Dligach, Timothy A. Miller, Danielle S. Bitterman, Guanhua Chen, Anoop M. Mayampurath, Matthew M. Churpek, Majid Afshar

CoRR, 2024

Mapping Bias in Vision Language Models: Signposts, Pitfalls, and the Road Ahead.

Kuleen Sasse, Shan Chen, Jackson Pond, Danielle S. Bitterman, John D. Osborne

CoRR, 2024

Wait, but Tylenol is Acetaminophen... Investigating and Improving Language Models' Ability to Resist Requests for Misinformation.

Shan Chen, Mingye Gao, Kuleen Sasse, Thomas Hartvigsen, Brian Anthony, Lizhou Fan, Hugo J. W. L. Aerts, Jack Gallifant, Danielle S. Bitterman

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

AIPatient: Simulating Patients with EHRs and LLM Powered Agentic Workflow.

Huizi Yu, Jiayan Zhou, Lingyao Li, Shan Chen, Jack Gallifant, Anye Shi, Xiang Li, Wenyue Hua, Mingyu Jin, Guang Chen, Yang Zhou, Zhao Li, Trisha Gupte, Ming-Li Chen, Zahra Azizi, Yongfeng Zhang, Themistocles L. Assimes, Xin Ma, Danielle S. Bitterman, Lin Lu, Lizhou Fan

CoRR, 2024

Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine.

Rui Yang, Yilin Ning, Emilia Keppo, Mingxuan Liu, Chuan Hong, Danielle S. Bitterman, Jasmine Chiat Ling Ong, Daniel Shu Wei Ting, Nan Liu

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

Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data.

Shan Chen, Jack Gallifant, Marco Guevara, Yanjun Gao, Majid Afshar, Timothy Miller, Dmitriy Dligach, Danielle S. Bitterman

CoRR, 2024

Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias.

Shan Chen, 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, Leo Anthony Celi, William G. La Cava, Danielle S. Bitterman

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Seeing Beyond Borders: Evaluating LLMs in Multilingual Ophthalmological Question Answering.

David S. Restrepo, Luis Filipe Nakayama, Robyn Gayle Dychiao, Chenwei Wu, Liam G. McCoy, Jose Carlo Artiaga, Marisa Cobanaj, João Matos, Jack Gallifant, Danielle S. Bitterman, Vincenz Ferrer, Yindalon Aphinyanaphongs, Leo Anthony Celi

Proceedings of the 12th IEEE International Conference on Healthcare Informatics, 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, Dmitriy Dligach, Timothy A. Miller, Danielle S. Bitterman, Matthew M. Churpek, Majid Afshar

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks.

Jack Gallifant, Shan Chen, Pedro Moreira, Nikolaj Munch, Mingye Gao, Jackson Pond, Leo Anthony Celi, Hugo J. W. L. Aerts, Thomas Hartvigsen, Danielle S. Bitterman

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

The impact of using an AI chatbot to respond to patient messages.

Shan Chen, 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, Maryam Lustberg, Majid Afshar, Danielle S. Bitterman

CoRR, 2023

Measuring Pointwise $\mathcal{V}$-Usable Information In-Context-ly.

Sheng Lu, Shan Chen, Yingya Li, Danielle S. Bitterman, Guergana Savova, Iryna Gurevych

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

Large Language Models to Identify Social Determinants of Health in Electronic Health Records.

Marco Guevara, Shan Chen, 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, Raymond H. Mak, Danielle S. Bitterman

CoRR, 2023

Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification.

Shan Chen, Yingya Li, Sheng Lu, Hoang Van, Hugo J. W. L. Aerts, Guergana K. Savova, Danielle S. Bitterman

CoRR, 2023

Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy.

Shan Chen, 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

Measuring Pointwise \mathcalV-Usable Information In-Context-ly.

Sheng Lu, Shan Chen, Yingya Li, Danielle S. Bitterman, Guergana Savova, Iryna Gurevych

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

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

2021

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, Michael T. Lu, Udo Hoffmann, Raymond H. Mak, Hugo J. W. L. Aerts

npj Digit. Medicine, 2021

2020

Extracting Relations between Radiotherapy Treatment Details.

Danielle S. Bitterman, Timothy Miller, David Harris, Chen Lin, Sean Finan, Jeremy L. Warner, Raymond H. Mak, Guergana Savova

Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020