A Content-Aware Chatbot based on GPT 4 provides trustworthy Recommendations for Cone Beam Computed Tomography Guidelines in Dental Imaging.

Russe, Maximilian Frederik; Rau, Alexander; Ermer, Michael Andreas; Rothweiler, René; Wenger, Sina; Klöble, Klara; Schulze, Ralf; Bamberg, Fabian; Schmelzeisen, Rainer; Reisert, Marco; Semper-Hogg, Wiebke (2024). A Content-Aware Chatbot based on GPT 4 provides trustworthy Recommendations for Cone Beam Computed Tomography Guidelines in Dental Imaging. Dento maxillo facial radiology, 53(2), pp. 109-114. British Institute of Radiology 10.1093/dmfr/twad015

Text twad015.pdf - Accepted Version Restricted to registered users only until 5 January 2025. Available under License Publisher holds Copyright. Download (1MB)

OBJECTIVES

To develop a content-aware chatbot based on GPT-3.5-Turbo and GPT-4 with specialized knowledge on the German S2 Cone-Beam CT (CBCT) dental imaging guideline and to compare the performance against humans.

METHODS

The LlamaIndex software library was used to integrate the guideline context into the chatbots. Based on the CBCT S2 guideline, 40 questions were posed to content-aware chatbots and early career and senior practitioners with different levels of experience served as reference. The chatbots' performance was compared in terms of recommendation accuracy and explanation quality. Chi-square test and one-tailed Wilcoxon signed rank test evaluated accuracy and explanation quality, respectively.

RESULTS

The GPT-4 based chatbot provided 100% correct recommendations and superior explanation quality compared to the one based on GPT3.5-Turbo (87.5% vs. 57.5% for GPT-3.5-Turbo; p = 0.003). Moreover, it outperformed early career practitioners in correct answers (p = 0.002 and p = 0.032) and earned higher trust than the chatbot using GPT-3.5-Turbo (p = 0.006).

CONCLUSIONS

A content-aware chatbot using GPT-4 reliably provided recommendations according to current consensus guidelines. The responses were deemed trustworthy and transparent and therefore facilitate the integration of artificial intelligence into clinical decision-making.

Interest & Impact

Downloads

1 since deposited on 08 Jan 2024
1 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item