Artificial Intelligence as a Digital Consultant: Evaluating Large Language Models for Patient Inquiries on Dental Caries

ABSTRACT Objective To evaluate the clinical accuracy, usefulness, global overall quality (GQS), and readability of ChatGPT, Gemini, and DeepSeek responses to patient questions regarding dental caries. Materials and Methods Fifty‐nine simulated patient questions concerning caries diagnosis, etiology, treatment, and prevention were queried in Turkish. Three restorative dentists independently evaluated the responses for accuracy, usefulness, and GQS. Readability was assessed using the Ateşman index. Statistical analyses included the intraclass correlation coefficient (ICC) for interrater reliability, the Friedman test for performance comparisons among the models, and Spearman's rank correlation to analyze the relationships between the clinical variables. Results Inter‐rater reliability was high across all criteria (ICC > 0.75). Significant performance differences existed among the models ( p < 0.001); Gemini achieved the highest overall clinical accuracy, usefulness, and GQS scores. ChatGPT produced the most readable texts, categorized generally as “easy to read” according to the Ateşman index. For DeepSeek, higher clinical accuracy significantly correlated with better readability ( p < 0.001). Conclusion Gemini offers the highest accuracy and quality as a digital preconsultation tool. However, AI tools should complement, not replace, professional dental advice.