Bitterman, Danielle S.

The TRIPOD-LLM reporting guideline for studies using large language models

Gallifant, J., Afshar, M., Ameen, S., Aphinyanaphongs, Y., Chen, S., Cacciamani, G., Demner-Fushman, D., Dligach, D., Daneshjou, R., Fernandes, C., et al. (2025) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 615

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

Guevara, M., Chen, S., Thomas, S., Chaunzwa, T. L., Franco, I., Kann, B. H., Moningi, S., Qian, J. M., Goldstein, M., Harper, S., et al. (2024) · npj Digital Medicine

Machine Learning in HealthcareTopic Modeling

Cited by 278

Use of Artificial Intelligence Chatbots for Cancer Treatment Information

Chen, S., Kann, B. H., Foote, M. B., Aerts, H. J. W. L., Savova, G. K., Mak, R. H., & Bitterman, D. S. (2023) · JAMA Oncology

Artificial Intelligence in Healthcare and EducationClinical practice guidelines implementation

Cited by 251

Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records

Savova, G. K., Danciu, I., Alamudun, F., Miller, T., Lin, C., Bitterman, D. S., Tourassi, G., & Warner, J. L. (2019) · Cancer Research

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 170

The effect of using a large language model to respond to patient messages

Chen, S., Guevara, M., Moningi, S., Hoebers, F., Elhalawani, H., Kann, B. H., Chipidza, F. E., Leeman, J., Aerts, H. J. W. L., Miller, T., et al. (2024) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationElectronic Health Records Systems

Cited by 147

When helpfulness backfires: LLMs and the risk of false medical information due to sycophantic behavior

Chen, S., Gao, M., Sasse, K., Hartvigsen, T., Anthony, B., Fan, L., Aerts, H., Gallifant, J., & Bitterman, D. S. (2025) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 112

Approaching autonomy in medical artificial intelligence

Bitterman, D. S., Aerts, H. J. W. L., & Mak, R. H. (2020) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 107

Evaluating the ChatGPT family of models for biomedical reasoning and classification

Chen, S., Li, Y., Lu, S., Van, H., Aerts, H. J. W. L., Savova, G. K., & Bitterman, D. S. (2024) · Journal of the American Medical Informatics Association

Topic ModelingBiomedical Text Mining and Ontologies

Cited by 91

Evaluation of ChatGPT Family of Models for Biomedical Reasoning and Classification

Chen, S., Li, Y., Lu, S., Van, H., Aerts, H. J., Savova, G. K., & Bitterman, D. S. (2023) · arXiv

Topic ModelingBiomedical Text Mining and Ontologies

Cited by 91

Collaborative Large Language Models for Automated Data Extraction in Living Systematic Reviews

Khan, M. A., Ayub, U., Naqvi, S. A. A., Khakwani, K. Z. R., Sipra, Z. B. R., Raina, A., Zou, S., He, H., Hossein, S. A., Hasan, B., et al. (2024) · Journal of the American Medical Informatics Association

Meta-analysis and systematic reviewsComputational and Text Analysis Methods

Cited by 54

Preventing unrestricted and unmonitored AI experimentation in healthcare through transparency and accountability

Comeau, D. S., Bitterman, D. S., & Celi, L. A. (2025) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 44

Toward Clinical-Grade Evaluation of Large Language Models

Moreno, A. C., & Bitterman, D. S. (2024) · International Journal of Radiation Oncology*Biology*Physics

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 28

Natural Language Processing to Automatically Extract the Presence and Severity of Esophagitis in Notes of Patients Undergoing Radiotherapy

Chen, S., Guevara, M., Ramirez, N., Murray, A., Warner, J. L., Aerts, H. J. W. L., Miller, T. A., Savova, G. K., Mak, R. H., & Bitterman, D. S. (2023) · JCO Clinical Cancer Informatics

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 20

Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks

Gallifant, J., Chen, S., Moreira, P. J. F., Munch, N., Gao, M., Pond, J., Celi, L. A., Aerts, H., Hartvigsen, T., & Bitterman, D. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 19

Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks

Gallifant, J., Chen, S., Moreira, P., Munch, N., Gao, M., Pond, J., Celi, L. A., Aerts, H., Hartvigsen, T., & Bitterman, D. (2024) · arXiv

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 19

When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?

Gao, Y., Myers, S., Chen, S., Dligach, D., Miller, T. A., Bitterman, D., Churpek, M., & Afshar, M. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 8

Natural Language Processing Methods to Empirically Explore Social Contexts and Needs in Cancer Patient Notes

Derton, A., Guevara, M., Chen, S., Moningi, S., Kozono, D. E., Liu, D., Miller, T. A., Savova, G. K., Mak, R. H., & Bitterman, D. S. (2023) · JCO Clinical Cancer Informatics

Machine Learning in HealthcareComputational and Text Analysis Methods

Cited by 8

Innovating global regulatory frameworks for generative AI in medical devices is an urgent priority

Ong, J. C. L., Ning, Y., Liu, M., Ma, Y., Zhao, L., Singh, K., Chang, R. T., Vogel, S., Lim, J. C. W., Tan, I. S. K., et al. (2026) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationHealthcare Regulation

Cited by 7

One shot at trust: building credible evidence for medical artificial intelligence

Kouzy, R., Hong, J. C., & Bitterman, D. S. (2025) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 4

Improving Patient Engagement: Is There a Role for Large Language Models?

Kouzy, R., & Bitterman, D. S. (2024) · International Journal of Radiation Oncology*Biology*Physics

Electronic Health Records SystemsArtificial Intelligence in Healthcare and Education

Cited by 3

MedBrowseComp: Benchmarking Medical Deep Research and Computer Use

Chen, S., Moreira, P., Xiao, Y., Schmidgall, S., Warner, J., Aerts, H., Hartvigsen, T., Gallifant, J., & Bitterman, D. S. (2025) · arXiv

Artificial Intelligence in Healthcare and EducationInformation Retrieval and Search Behavior

Cited by 0