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A content-aware chatbot based on GPT 4 provides trustworthy recommendations for Cone-Beam CT guidelines in dental imaging

Maximilian Frederik Russe, Alexander Rau, Michael Andreas Ermer, René Rothweiler, Sina Wenger, Klara Klöble, Ralf Schulze, Fabian Bamberg, Rainer Schmelzeisen, Marco Reisert, Wiebke Semper-Hogg

2024Dentomaxillofacial Radiology21 citationsDOIOpen Access PDF

Abstract

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 = .003). Moreover, it outperformed early career practitioners in correct answers (P = .002 and P = .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.

Topics & Concepts

ChatbotGuidelineContext (archaeology)Computer scienceWilcoxon signed-rank testTest (biology)Cone beam computed tomographyMedical physicsMedicineArtificial intelligenceRadiologyComputed tomographyPathologyInternal medicinePaleontologyMann–Whitney U testBiologyArtificial Intelligence in Healthcare and EducationAI in Service InteractionsElectronic Health Records Systems