Fries, Jason A.

A Systematic Review of Testing and Evaluation of Healthcare Applications of Large Language Models (LLMs)

Bedi, S., Liu, Y., Orr-Ewing, L., Dash, D., Koyejo, S., Callahan, A., Fries, J. A., Wornow, M., Swaminathan, A., Lehmann, L. S., et al. (2024) · JAMA

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 738

Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review

Bedi, S., Liu, Y., Orr-Ewing, L., Dash, D., Koyejo, S., Callahan, A., Fries, J. A., Wornow, M., Swaminathan, A., Lehmann, L. S., et al. (2025) · JAMA

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 662

Multitask Prompted Training Enables Zero-Shot Task Generalization

Sanh, V., Webson, A., Raffel, C., Bach, S. H., Sutawika, L., Alyafeai, Z., Chaffin, A., Stiegler, A., Scao, T. L., Raja, A., et al. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 612

The shaky foundations of large language models and foundation models for electronic health records

Wornow, M., Xu, Y., Thapa, R., Patel, B., Steinberg, E., Fleming, S., Pfeffer, M. A., Fries, J., & Shah, N. H. (2023) · npj Digital Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 324

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

Bach, S., Sanh, V., Yong, Z. X., Webson, A., Raffel, C., Nayak, N. V., Sharma, A., Kim, T., Bari, M. S., Fevry, T., et al. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

Natural Language Processing TechniquesTopic Modeling

Cited by 178

Language models are an effective representation learning technique for electronic health record data

Steinberg, E., Jung, K., Fries, J. A., Corbin, C. K., Pfohl, S. R., & Shah, N. H. (2021) · Journal of Biomedical Informatics

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 132

Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine

Guo, L. L., Pfohl, S. R., Fries, J., Johnson, A. E. W., Posada, J., Aftandilian, C., Shah, N., & Sung, L. (2022) · Scientific Reports

Machine Learning in HealthcareDomain Adaptation and Few-Shot Learning

Cited by 103

Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine

Guo, L. L., Pfohl, S. R., Fries, J., Posada, J., Fleming, S. L., Aftandilian, C., Shah, N., & Sung, L. (2021) · Applied Clinical Informatics

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 96

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

Fleming, S. L., Lozano, A., Haberkorn, W. J., Jindal, J. A., Reis, E., Thapa, R., Blankemeier, L., Genkins, J. Z., Steinberg, E., Nayak, A., et al. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 66

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

Fleming, S. L., Lozano, A., Haberkorn, W. J., Jindal, J. A., Reis, E. P., Thapa, R., Blankemeier, L., Genkins, J. Z., Steinberg, E., Nayak, A., et al. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 65

Holistic evaluation of large language models for medical tasks with MedHELM

Bedi, S., Cui, H., Fuentes, M., Unell, A., Wornow, M., Banda, J. M., Kotecha, N., Keyes, T., Mai, Y., Oez, M., et al. (2026) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 59

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

Bach, S. H., Sanh, V., Yong, Z.-X., Webson, A., Raffel, C., Nayak, N. V., Sharma, A., Kim, T., Bari, M. S., Fevry, T., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 21

BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing

Fries, J. A., Weber, L., Seelam, N., Altay, G., Datta, D., Garda, S., Kang, M., Su, R., Kusa, W., Cahyawijaya, S., et al. (2022) · arXiv

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 17