Brush, byte, and bot: quality comparison of artificial intelligence-generated pediatric dental advice across ChatGPT, Gemini, and Copilot.

IF 3.1 Q1 DENTISTRY, ORAL SURGERY & MEDICINE

Frontiers in oral health Pub Date : 2025-08-15 eCollection Date: 2025-01-01 DOI:10.3389/froh.2025.1652422

Deepika Kapoor, Deepanshu Garg, Santosh Kumar Tadakamadla

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Abstract

Introduction: Artificial intelligence (AI) tools such as ChatGPT, Google Gemini, and Microsoft Copilot are increasingly relied upon by parents for immediate guidance on pediatric dental concerns. This study evaluated and compared the response quality of these AI platforms in addressing real-world parental queries related to pediatric dentistry, including early tooth extraction, space maintenance, and the decision to consult a pediatric or a general dentist.

Methods: A structured 30-question survey was developed and submitted to each AI model, and their responses were anonymized and assessed by pediatric dental experts using a standardized rubric across five key domains: clinical accuracy, clarity, completeness, relevance, and absence of misleading information.

Results: Statistically significant differences were found across all five domains (p < .001), with ChatGPT consistently achieving the highest scores. Multivariate analysis (MANOVA) confirmed a strong overall effect of the AI model on response quality (Pillai's Trace = 0.892, p < .001), supporting ChatGPT's superior performance in providing accurate, relevant, and comprehensive pediatric dental advice.

Discussion: While AI technologies show potential as clinical decision support systems, their variable performance reinforces the need for expert oversight. Future AI development should focus on optimizing response quality and safety to ensure effective and trustworthy digital health communication for pediatric dental care.

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刷、字节和机器人：ChatGPT、Gemini和Copilot中人工智能生成的儿科牙科建议的质量比较。

人工智能（AI）工具，如ChatGPT、谷歌Gemini和Microsoft Copilot，越来越多的父母依赖于儿童牙科问题的即时指导。本研究评估并比较了这些人工智能平台在解决现实世界中与儿童牙科相关的父母问题时的响应质量，包括早期拔牙、空间维护以及咨询儿科或普通牙医的决定。方法：开发了一份包含30个问题的结构化调查，并将其提交给每个人工智能模型，儿童牙科专家使用五个关键领域的标准化标准对他们的回答进行匿名评估：临床准确性、清晰度、完整性、相关性和缺乏误导性信息。讨论：虽然人工智能技术显示出作为临床决策支持系统的潜力，但其不同的表现加强了对专家监督的需求。未来的人工智能发展应着眼于优化响应质量和安全性，以确保有效和值得信赖的儿童牙科保健数字健康通信。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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