Assessment of the Accuracy of Modern Artificial Intelligence Chatbots in Responding to Endodontic Queries

This study aims to compare the accuracy of modern AI chatbots, including Gemini 1.5 Flash, Gemini 1.5 Pro, ChatGPT-3.5 and ChatGPT-4, in responding to endodontic questions and supporting clinicians. Forty yes/no questions covering 12 endodontic topics were formulated by three experts. Each question was presented to the AI models on the same day, with a new chat session initiated for each. The agreement between chatbot responses and expert consensus was assessed using Cohen's kappa test (p < 0.05). ChatGPT-3.5 demonstrated the highest accuracy (80%), followed by ChatGPT-4 (77.5%), Gemini 1.5 Pro (72.5%) and Gemini 1.5 Flash (60%). The agreement levels ranged from weak (ChatGPT models) to minimal (Gemini Flash). The findings indicate variability in chatbot performance, with ChatGPT models outperforming Gemini. However, reliance on AI-generated responses for clinical decision-making remains questionable. Future studies should incorporate more complex clinical scenarios and broader analytical approaches to enhance the assessment of AI chatbots in endodontics.

Authors

Institutions

Publication Details

Journal
Australian Endodontic Journal
Published
2025-08-20
DOI
https://doi.org/10.1111/aej.70012
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of the Accuracy of Modern Artificial Intelligence Chatbots in Responding to Endodontic Queries

Ayşe Tuğba Eminsoy Avcı, Salih Düzgün, Tuğrul Aslan, Kübra Nur Hekimoğlu et al.
1 citations
Australian Endodontic Journal
Artificial Intelligence in Healthcare and Education
0.65
article

Assessment of the Accuracy of Modern Artificial Intelligence Chatbots in Responding to Endodontic Queries

Ayşe Tuğba Eminsoy Avcı, Salih Düzgün, Tuğrul Aslan, Kübra Nur Hekimoğlu, Melis Çakar
article en
1 citations

Abstract

This study aims to compare the accuracy of modern AI chatbots, including Gemini 1.5 Flash, Gemini 1.5 Pro, ChatGPT-3.5 and ChatGPT-4, in responding to endodontic questions and supporting clinicians. Forty yes/no questions covering 12 endodontic topics were formulated by three experts. Each question was presented to the AI models on the same day, with a new chat session initiated for each. The agreement between chatbot responses and expert consensus was assessed using Cohen's kappa test (p < 0.05). ChatGPT-3.5 demonstrated the highest accuracy (80%), followed by ChatGPT-4 (77.5%), Gemini 1.5 Pro (72.5%) and Gemini 1.5 Flash (60%). The agreement levels ranged from weak (ChatGPT models) to minimal (Gemini Flash). The findings indicate variability in chatbot performance, with ChatGPT models outperforming Gemini. However, reliance on AI-generated responses for clinical decision-making remains questionable. Future studies should incorporate more complex clinical scenarios and broader analytical approaches to enhance the assessment of AI chatbots in endodontics.

Australian Endodontic JournalVol. 51(3)
Erciyes University (TR)
Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare and Education
0.65
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.