Performance of large language models in fluoride-related dental knowledge: a comparative evaluation study of ChatGPT-4, Claude 3.5 Sonnet, Copilot, and Grok 3.

ABSTRACT:

Background

Large language models (LLMs) have rapidly emerged as valuable tools in medical and dental education that support clinical reasoning, patient communication, and academic instruction. However, their effectiveness in conveying specialized content, such as fluoride-related dental knowledge, requires a thorough evaluation. This study assesses the performance of four advanced LLMs-ChatGPT-4 (OpenAI), Claude 3.5 Sonnet (Anthropic), Microsoft Copilot, and Grok 3 (xAI)-in addressing fluoride-related topics in dentistry.

Methods

A cross-sectional comparative analysis was conducted using a mixed methods framework. Fifty multiple-choice questions (MCQs) and ten open-ended questions covering fluoride chemistry, clinical applications, and safety concerns were administered to ea

SUBMITTER: Biswas R 

PROVIDER: S-EPMC12800559 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature