What question did this study set out to answer?

This study evaluates the accuracy, quality, and readability of AI chatbots in dental anesthesia and sedation.

May 30, 2026Open Access

Evaluation of the accuracy, quality, and readability of large language models on local anesthesia and general anesthesia-sedation in dentistry

Puntos clave

This study evaluates the accuracy, quality, and readability of AI chatbots in dental anesthesia and sedation.
Sixty questions based on ADA and ASA guidelines were created, split between patient and professional queries.
Four AI models were assessed by four blinded pediatric dentists using a quality scale and readability measures like FRE and FKGL.
Inter-rater reliability was established using the intraclass correlation coefficient (ICC).
DeepSeek-R1 showed the highest accuracy and inter-rater agreement (p < 0.001).
Gemini 2.0 Flash had the best readability scores, while DeepSeek-R1 was less readable (p = 0.012).
ChatGPT-3.5's readability varied by question type, showing better scores for multiple-choice questions (p = 0.027).

Resumen

This study aims to compare the responses provided by commonly used artificial intelligence-based chatbots such as ChatGPT-3.5, ChatGPT-4o, Gemini 2.0 Flash, and DeepSeek-R1 about dental local anesthesia, sedation, and general anesthesia in terms of accuracy, reliability, and readability. Sixty questions were created from the American Dental Association (ADA) and American Society of Anesthesiologists (ASA) guidelines. Thirty were patient questions, thirty professional questions. Each group contained ten open-ended, ten multiple-choice, and ten true/false questions. The questions were submitted to ChatGPT-3.5, ChatGPT-4o, DeepSeek-R1, and Gemini 2.0 Flash. Four blinded pediatric dentists evaluated the answers with a modified global quality scale. Clinical safety and risk analysis were evaluated using a 3-point Likert scale. Readability was measured by Flesch Reading Ease Score (FRE) and Flesch–Kincaid Grade Level (FKGL). The intraclass correlation coefficient (ICC) tested inter-rater reliability. Significance was set at p 0.05). Chatbot performance depends on both question type and evaluation criteria. DeepSeek-R1 excelled in accuracy and quality. Gemini 2.0 Flash produced the clearest, patient-friendly responses. AI chatbots can support communication in dental anesthesia. Choosing the right model may improve education, assist clinical training, and guide professional decisions.

Preguntar a la IA

Me gusta

Guardar

Ver artículo completo