Artificial intelligence in dental clinical decision support: Concept, challenges, and progress.
Abstract
Purpose
In this review, we propose and elaborate on the conceptual framework of "decision support intelligence" (DSI) in dentistry. We aimed to define DSI as the intelligent execution of evidence-based clinical decision trees, outline a preliminary implementation pathway, identify key technical challenges hindering its development, and summarize the current research progress across major dental specialties to guide future artificial intelligence (AI) integration in clinical decision-making. STUDY SELECTION We searched for studies using major databases including PubMed, Web of Science, and IEEE Xplore, to construct a coherent conceptual framework and illustrate the key arguments.
Results
The transition toward intelligent dentistry remains incomplete, with "operational intelligence" maturing while DSI lags. This review is the first to report the core concept of DSI as an intelligent execution of decision trees that simulate clinical reasoning. It outlines the preliminary implementation strategies and key developmental challenges.
Conclusions
This review may accelerate the translation of AI from research to practical clinical tools, ultimately supporting dentists in making more standardized, efficient, and evidence-based decisions, reducing workload, and minimizing errors, particularly in resource-variable settings.