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February 6, 2026BMC Oral Health3 citationsOpen Access

Artificial intelligence for binary dental caries diagnosis using intraoral images and dental radiographs: a systematic review and meta-analysis

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JLJing LaiSGShanshan GuoKWKe Wang

Key Points

  • Assess the effectiveness of artificial intelligence for diagnosing dental caries using different imaging techniques.
  • Conducted a systematic review and meta-analysis of existing AI diagnostic models.
  • Evaluated diagnostic accuracy across various imaging modalities and analytical units.
  • Analyzed the heterogeneity and quality of included studies.
  • AI models demonstrated good diagnostic accuracy for caries detection.
  • Substantial heterogeneity and limitations in study quality were noted.
  • AI-based systems could be useful as decision-support tools, requiring further validation.

Abstract

AI models showed good diagnostic accuracy for caries detection across imaging modalities and analytical units. However, given the substantial heterogeneity and limitations in study quality and reference standards, these summary estimates should be interpreted with caution. AI-based systems may serve as complementary decision-support tools in clinical practice, but further standardization, external validation, and high-quality multicenter studies are required before broad clinical implementation.

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Cite This Study

Lai et al. (2026) studied this question.

synapsesocial.com/papers/698584f98f7c464f230082f0https://doi.org/10.1186/s12903-026-07770-4
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