ArticleProceedings (Baylor University. Medical Center)2026
Evaluating the quality of artificial intelligence responses to psoriasis-related clinical and patient questions: a comparative study of ChatGPT, Gemini, and Microsoft Copilot.
Article in Proceedings (Baylor University. Medical Center), 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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3 authors.
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Abstract
backgroundPatient use of artificial intelligence (AI) chatbots for dermatologic information is increasing, but their performance on psoriasis-related questions across clinically distinct domains remains unclear. We compared ChatGPT (GPT-5.3 Instant), Gemini (Gemini 3 Flash), and Microsoft Copilot using a multidimensional scoring framework.
methodsFifty-four psoriasis-related questions were submitted to each model across diagnostic (n = 12), treatment (n = 12), and patient-question (n = 30) categories. Three board-certified dermatologists independently scored responses for accuracy, evidence consistency, completeness, and clinical safety (maximum score, 8).
resultsInterrater agreement was substantial to almost perfect (κ = 0.743 for ChatGPT, 0.830 for Gemini, and 0.844 for Copilot). Overall mean scores differed significantly: 7.36 ± 0.97, 7.77 ± 0.77, and 7.05 ± 1.09, respectively (Friedman
conclusionsAll models showed high clinical safety, but Gemini provided the most complete and highest-quality responses. The observation that models may provide accurate yet clinically incomplete responses, particularly for treatment content, emphasizes the need for physician oversight when AI-generated information is used in dermatological practice.
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