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Review
. 2022 Apr 26;12(5):1083.
doi: 10.3390/diagnostics12051083.

Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)-A Systematic Review

Sanjeev B Khanagar  1   2 , Khalid Alfouzan  2   3 , Mohammed Awawdeh  1   2 , Lubna Alkadi  2   3 , Farraj Albalawi  1   2 , Abdulmohsen Alfadley  2   3
Affiliations
Review

Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)-A Systematic Review

Sanjeev B Khanagar et al. Diagnostics (Basel). .

Abstract

Evolution in the fields of science and technology has led to the development of newer applications based on Artificial Intelligence (AI) technology that have been widely used in medical sciences. AI-technology has been employed in a wide range of applications related to the diagnosis of oral diseases that have demonstrated phenomenal precision and accuracy in their performance. The aim of this systematic review is to report on the diagnostic accuracy and performance of AI-based models designed for detection, diagnosis, and prediction of dental caries (DC). Eminent electronic databases (PubMed, Google scholar, Scopus, Web of science, Embase, Cochrane, Saudi Digital Library) were searched for relevant articles that were published from January 2000 until February 2022. A total of 34 articles that met the selection criteria were critically analyzed based on QUADAS-2 guidelines. The certainty of the evidence of the included studies was assessed using the GRADE approach. AI has been widely applied for prediction of DC, for detection and diagnosis of DC and for classification of DC. These models have demonstrated excellent performance and can be used in clinical practice for enhancing the diagnostic performance, treatment quality and patient outcome and can also be applied to identify patients with a higher risk of developing DC.

Keywords: artificial intelligence; dental caries; detection; diagnosis; prediction.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Flow chart for screening and selection of articles.
Figure 2
Figure 2
QUADAS-2 assessment of the individual risk of bias domains and applicability concerns.
See this image and copyright information in PMC

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