Diagnostic accuracy of artificial intelligence for detecting dental caries in camera and smartphone photographs

Natalia Rincón Gómez, Rolando Andrés Figueroa Andrade and Diana Vélez Santana

SAP Artificial Intelligence in Dentistry, 2026

Abstract: Introduction: Artificial intelligence applied to intraoral photographs could extend caries detection beyond the dental chair, but its accuracy on camera and smartphone images has not been consolidated. Methods: A systematic review was conducted, including studies reporting the diagnostic accuracy of artificial intelligence for detecting dental caries on intraoral photographs taken with cameras or smartphones. Results: Seventeen primary studies published in 2025 and 2026 were included. Reported accuracy was moderate to high but varied by acquisition device and lesion severity: detection on camera-acquired photographs was generally more accurate than on smartphone photographs, and cavitated lesions were detected more accurately than initial lesions. General-purpose multimodal models underperformed dedicated convolutional models. Conclusions: Artificial intelligence detects dental caries on intraoral photographs with moderate to high accuracy, but the evidence is young and dominated by single-institution studies. Accuracy is higher for camera than smartphone images and for cavitated than initial lesions, and dedicated models outperform general-purpose ones.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cwf:aidart:aid2026149

DOI: 10.62486/aid2026149

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