ArticleMayo Clinic proceedings. Digital health2026
Arkangel AI, OpenEvidence, ChatGPT, Medisearch: Are They Objectively up to Medical Standards? A Real-Life Assessment of LLM Chatbots in Health Care.
Article in Mayo Clinic proceedings. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
6 authors.
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Abstract
Objective: To compare the performance of 4 large language model chatbots in response time and quality of clinical answers, evaluated by specialists using predefined validity criteria. Participants and Methods: Between June 1 and September 20, 2025, four clinical vignettes (orthopedics, pediatrics, gynecology, and psychiatry) were developed by independent experts and answered by 4 conversational agents: Arkangel AI, OpenEvidence, ChatGPT, and Medisearch. Each vignette included 4 questions (diagnosis, clinical management, research, and general knowledge). Responses were independently evaluated by external clinicians using an 8-criterion Likert scale assessing correctness, consensus agreement, absence of bias, adherence to standards of care, timeliness, patient safety, authenticity of cited references, and contextual appropriateness. Response times were summarized using medians and interquartile ranges. Results: A total of 128 question-answer pairs (1024 evaluations) were analyzed. Overall satisfaction ranged from 71.1% (727) to 93% (952) across agents, with statistically significant differences (Kruskal-Wallis Conclusion: Large language model chatbots showed substantial variability across validity dimensions when assessed using expert clinical judgment, supporting the need for standardized, multidimensional evaluation frameworks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.