Quality and Reliability of AI Information on Dental Implant Failure: A Comparative Multi-Model Analysis
Abstract
OBJECTIVE: This study aimed to develop a consensus-based set of patient questions on dental implant failure and to compare the clarity, quality, accuracy, reliability, and readability of responses generated by 4 widely used AI chatbots: ChatGPT-4, DeepSeek-R1, Microsoft Copilot, and Google Gemini. METHODS: Twenty-three expert-validated questions were derived from the EAO 2021 and ICOI Pisa Consensus reports and independently submitted to each AI model under standardized, non-personalized conditions. Responses were assessed using CLEAR criteria, mGQS, a 5-point accuracy scale, the first 8 DISCERN items, and Flesch-based readability indices. Nonparametric tests were used for intermodel comparisons. RESULTS: AI models demonstrated significant variability in performance. Gemini achieved the highest accuracy ( P
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Electronic Health Records Systems
AI in Service Interactions
Publication details
- Journal / source
- Journal of Craniofacial Surgery
- Publisher
- Ovid Technologies (Wolters Kluwer Health)
- Volume
- 37
- Issue
- 3/4
- Pages
- 675–680
- Publication date
- 17 January 2026
- Language
- EN