Aphinyanaphongs, Yindalon

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

Health system-scale language models are all-purpose prediction engines

Jiang, L. Y., Liu, X. C., Nejatian, N. P., Nasir-Moin, M., Wang, D., Abidin, A., Eaton, K., Riina, H. A., Laufer, I., Punjabi, P., et al. (2023) · Nature

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 460

Generative Artificial Intelligence to Transform Inpatient Discharge Summaries to Patient-Friendly Language and Format

Zaretsky, J., Kim, J. M., Baskharoun, S., Zhao, Y., Austrian, J., Aphinyanaphongs, Y., Gupta, R., Blecker, S. B., & Feldman, J. (2024) · JAMA Network Open

Artificial Intelligence in Healthcare and EducationHealth Literacy and Information Accessibility

Cited by 303

Medical large language models are vulnerable to data-poisoning attacks

Alber, D. A., Yang, Z., Alyakin, A., Yang, E., Rai, S., Valliani, A. A., Zhang, J., Rosenbaum, G. R., Amend-Thomas, A. K., Kurland, D. B., et al. (2025) · Nature Medicine

Adversarial Robustness in Machine LearningMisinformation and Its Impacts

Cited by 242

Text Categorization Models for High-Quality Article Retrieval in Internal Medicine

Aphinyanaphongs, Y. (2004) · Journal of the American Medical Informatics Association

Information Retrieval and Search BehaviorText and Document Classification Technologies

Cited by 177

Development and Validation of a Machine Learning-Based Decision Support Tool for Residency Applicant Screening and Review

Burk-Rafel, J., Reinstein, I., Feng, J., Kim, M. B., Miller, L. H., Cocks, P. M., Marin, M., & Aphinyanaphongs, Y. (2021) · Academic Medicine

Medical Education and AdmissionsAI and HR Technologies

Cited by 65

Development of a Clinical Reasoning Documentation Assessment Tool for Resident and Fellow Admission Notes: a Shared Mental Model for Feedback

Schaye, V., Miller, L., Kudlowitz, D., Chun, J., Burk-Rafel, J., Cocks, P., Guzman, B., Aphinyanaphongs, Y., & Marin, M. (2022) · Journal of General Internal Medicine

Clinical Reasoning and Diagnostic SkillsInnovations in Medical Education

Cited by 54

General-purpose large language models outperform specialized clinical AI tools on medical benchmarks

Vishwanath, K., Alyakin, A., Ghosh, M., Hage, A., Neifert, S. N., Orillac, C., Mandelberg, N. J., Khan, H. A., Lee, J. V., Yao, J. J., et al. (2026) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 49

Development and Validation of a Machine Learning Model for Automated Assessment of Resident Clinical Reasoning Documentation

Schaye, V., Guzman, B., Burk-Rafel, J., Marin, M., Reinstein, I., Kudlowitz, D., Miller, L., Chun, J., & Aphinyanaphongs, Y. (2022) · Journal of General Internal Medicine

Clinical Reasoning and Diagnostic SkillsArtificial Intelligence in Healthcare and Education

Cited by 44

The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT

Small, W. R., Malhotra, K., Major, V. J., Wiesenfeld, B., Lewis, M., Grover, H., Tang, H., Banerjee, A., Jabbour, M. J., Aphinyanaphongs, Y., et al. (2024) · PLOS Digital Health

Artificial Intelligence in Healthcare and EducationBiomedical and Engineering Education

Cited by 17