Evaluating Artificial Intelligence Chatbots for Patient Education on Thyroid Radiofrequency Ablation: An Analysis of Accuracy, Quality, and Readability

Abstract

BACKGROUND: Artificial intelligence (AI) chatbots are increasingly being used by patients to obtain medical information. Comparison between platforms with specialty-specific physician assessment remains limited. This study compares the quality, factual accuracy, readability, and consistency of responses generated by four publicly available AI chatbots when answering patient-centered questions about thyroid radiofrequency ablation (RFA). METHODS: < 0.05. RESULTS: < 0.005). ChatGPT responses were significantly longer and more readable. Score variability across questions was lowest for Gemini. Copilot and Perplexity ranked lowest across most domains. Question-level analysis identified specific prompts that best discriminated between platforms. CONCLUSIONS: AI chatbot performance varied across platforms for thyroid RFA queries. Chatbots were generally reliable for straightforward factual information but were less dependable for judgment or context-dependent assessments. These AI tools should supplement, not replace, clinician-vetted patient education and institutional materials.

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