How accurate and useful are AI chatbots in interpreting pediatric intraoral photographs?

Abstract

Accurate recognition of oral conditions is essential for parents to seek timely dental care for their children. However, many parents struggle to identify common pediatric dental problems. Artificial intelligence (AI) tools capable of interpreting clinical images may help bridge this knowledge gap by providing understandable and actionable guidance. This study assessed the diagnostic accuracy, consistency, and communication quality of AI-generated responses to intraoral photographs of pediatric dental conditions. Three large language models —ChatGPT-4o, ChatGPT-5, and Gemini 2.0 Flash—were tested using standardized intraoral photographs of common pediatric dental conditions. Each model was prompted with the same diagnostic question (What is this condition, and what should I do? ). Responses were evaluated for diagnostic accuracy, understandability, actionability, and overall quality using the Patient Education Materials Assessment Tool (PEMAT) and the Global Quality Scale (GQS). Statistical comparisons were performed using the Kruskal–Wallis test ( p < 0.05). ChatGPT-4o achieved the highest diagnostic accuracy (81.48%), followed by ChatGPT-5 (75.93%) and Gemini 2.0 Flash (35.19%) ( p < 0.001). Significant differences were also observed in PEMAT and GQS scores ( p < 0.001). ChatGPT-4o and ChatGPT-5 demonstrated moderate-to-high accuracy, yet variability in communication quality persists. These tools may assist parent education but cannot replace professional evaluation.