ArticleLaryngoscope investigative otolaryngology2025
Evaluation of Large Language Models' Concordance With Guidelines on Olfaction.
Article in Laryngoscope investigative otolaryngology, 2025. 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
7 authors.
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Abstract
Objective: To assess the concordance of artificial intelligence (AI)-generated information with the 2022 International Consensus Statement on Allergy and Rhinology: Olfaction (ICAR-O). Methods: Forty-two guidelines were extracted from the ICAR-O. Each guideline was converted into a question, which was presented to ChatGPT version 4.o and Google Gemini. Concordance was deemed an agreement between the AI response and the clinical recommendation. Credibility was granted if the AI platform provided a credible resource. Accuracy was graded on a Likert scale (0: entirely inaccurate information, 1: mix of accurate and inaccurate information, 2: entirely accurate information). Statistical analysis was performed. Results: A total of 84 responses were generated. The mean accuracy of the ChatGPT and Gemini responses was 1.85 and 1.48 out of 2, respectively, indicating that the responses contained a mix of accurate and inaccurate information. ChatGPT responses were significantly more accurate than Gemini responses ( Conclusion: ChatGPT provided more accurate information than Gemini on olfaction. However, overall, both platforms did not consistently align with clinical guidelines. AI platforms require further evaluation before clinical implementation or use as educational adjuncts. Level of Evidence: N/A.
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