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Updated: Sep 18, 2025

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Deep Learning Applications in Dental Image-Based Diagnostics: A Systematic Review.

Osama Khattak1, Ahmed Shawkat Hashem2, Mohammed Saad Alqarni3

  • 1Department of Restorative Dentistry, College of Dentistry, Jouf University, Sakaka 72311, Saudi Arabia.

Healthcare (Basel, Switzerland)
|June 26, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) in dentistry shows 82% diagnostic accuracy, improving dental caries detection. Challenges include data bias and ethical concerns, requiring careful integration for future dental healthcare.

Keywords:
AI modelsartificial intelligencedental sciencesdiagnosismachine learning

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Area of Science:

  • Dental Informatics
  • Artificial Intelligence in Medicine
  • Systematic Review and Meta-analysis

Background:

  • Artificial intelligence (AI) is increasingly utilized in dentistry for diagnosis, treatment planning, and prognosis.
  • This review systematically assesses AI models in dentistry, evaluating their performance, limitations, and future integration potential.

Purpose of the Study:

  • To identify and evaluate AI models applied in dentistry.
  • To assess the diagnostic accuracy and predictive performance of these AI models.
  • To discuss the challenges and ethical considerations for AI adoption in dental practice.

Main Methods:

  • Systematic literature search of PubMed, Scopus, and Cochrane Library.
  • Meta-analysis of 20 selected studies out of 947 identified papers.
  • Assessment of diagnostic accuracy, predictive performance, and potential biases of AI models.

Main Results:

  • AI models achieved an average diagnostic accuracy of 82%, predominantly using artificial neural networks (ANNs) and convolutional neural networks (CNNs).
  • Significant improvements in diagnosing dental caries compared to traditional methods were observed.
  • AI shows promise in detecting various conditions like bone loss, lesions, cysts, and in orthodontic assessments, but faces challenges in data bias, cost, and data security.

Conclusions:

  • AI holds transformative potential for dentistry, enhancing diagnostic precision and treatment planning.
  • Critical evaluation of AI's benefits, drawbacks, and ethical implications is necessary before widespread clinical adoption.
  • Future research should address barriers related to data, cost, and security to facilitate effective AI utilization in dental healthcare.