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This paper is in the following e-collection/theme issue:

Letters to the Editor (17) Ontologies, Classifications, and Coding (405) Machine Learning (2996) Development and Evaluation of Research Methods, Instruments and Tools (1226) Chatbots and Conversational Agents (1117) Generative Language Models Including ChatGPT (1373) Health Risk and Perception in Cognitive Reasoning (36) Applications of AI (808)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/90759, first published .
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Toward Retrieval-Grounded Evaluation for Conversational Large Language Model–Based Risk Assessment

Toward Retrieval-Grounded Evaluation for Conversational Large Language Model–Based Risk Assessment

Authors of this article:

Yihan Hu1 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Roshani M, Zhou X, Qiang Y, Suresh S, Hicks S, Sethuraman U, Zhu D. Authors’ Reply: Toward Retrieval-Grounded Evaluation for Conversational Large Language Model–Based Risk Assessment. JMIR AI 2026;5:e91981 View
  2. Cai C, Zhu G, Zhou S, Ng O, Duell J, Ho W, Chen D, Lee B, Li F, Liu S, Sudarshan V, Wang L, Choi C, Fan X. A Competency Framework for Medical AI Education: Mixed Methods Study. JMIR Medical Education 2026;12:e91116 View
  3. Kim M, An Y, Jeon M, Lee Y, Lahcine O, Kim H, Lee S, Lee S, Yang J, Jeon S, Jung D, Cho C. Mapping Practice-Based Signals of Generative AI in Psychiatric Care: Qualitative Study of Korean Psychiatrists’ Experiences, Interpretations, and Implementation Priorities. Journal of Medical Internet Research 2026;28:e96556 View
  4. Kumar A, Varshney L. Training AI Models for Aesthetic Facial Evaluation: Focused Review and Framework to Mitigate Homogenizing Bias. Journal of Medical Internet Research 2026;28:e95452 View