Key result
ChatGPT-4o and Grok-3 demonstrate comparable accuracy and clarity on mitral regurgitation questions.
Why the study?
Previous cardiology studies on large language models for patient education and physician assistance have focused predominantly on ChatGPT, with limited research evaluating the performance of Grok in responding to frequently asked questions about mitral regurgitation.
Does ChatGPT-4o improve accuracy, ease of understanding, and overall satisfaction compared with Grok-3 in responding to frequently asked questions about mitral regurgitation?
Does ChatGPT-4o improve accuracy, ease of understanding, and overall satisfaction compared with Grok-3 in responding to frequently asked questions about mitral regurgitation?
This study evaluates and compares the performance of two large language models, ChatGPT-4o and Grok-3, in providing patient education for mitral regurgitation.
Answers are grounded in this paper and cite their sources.
AI chatbots warrant evaluation for mitral regurgitation education; leaves open standardized validation before clinical use.
Since the release of ChatGPT in 2022, large language models (LLMs) have seen substantial growth in medical applications, including patient education and physician assistance. Previous studies in cardiology have predominantly focused on ChatGPT, with limited research evaluating the performance of Grok. This study aims to assess and compare the accuracy, ease of understanding, and overall satisfaction of ChatGPT-4o and Grok-3 in responding to frequently asked questions about mitral regurgitation (MR).
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Zein et al. (2026) studied Mitral regurgitation. ChatGPT-4o vs. Grok-3 was evaluated on Accuracy, ease of understanding, and overall satisfaction of responses to frequently asked questions about mitral regurgitation.
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