Assessing the Role of Artificial Intelligence in Caries Detection and Clinical Decision-Making: A Scoping Review

Abstract

BACKGROUND: Artificial intelligence (AI) support is expected to increase accuracy and improve treatment plans in dentistry. Nevertheless, AI's ability to promote better oral healthcare is underexplored. This scoping review explores the influence of AI in supporting dental professionals with caries detection and decision-making regarding interventions. SUMMARY: Primary articles indexed on PubMed, Web of Science, Embase, Scopus, and Cochrane Library were searched until August 2025. Studies reporting the differences between participants' caries diagnosis process and decision-making with and without AI were included. Studies only reporting algorithm accuracy, in vitro studies, or studies without an outcome related to caries detection with AI support were excluded. No time and language limits were imposed. Outcomes regarding the influence of AI on the diagnostics process and decision-making were retrieved and narratively summarised. KEY MESSAGES: Thirteen publications were included. Number of participants ranged from 3 to 74, comprising dentists with varying experience and expertise and dental students. Results showed that AI enhances sensitivity, though its impact on specificity varies (10 studies). AI can promote unnecessary interventions for early-stage caries lesions (1 study). AI increased assessment time in two out of three cases (3 studies). AI's cost-effectiveness is uncertain, as greater sensitivity did not lead to better economic outcomes (1 study). In conclusion, AI has the potential to improve diagnostics and influence treatment choices, but current evidence is limited and inconsistent regarding its impact on specificity, decision quality, and cost-effectiveness. Longitudinal studies in clinical settings with long-term follow-ups are needed to understand AI's impact on decision-making.

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