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Review
. 2021 Jan;16(1):508-522.
doi: 10.1016/j.jds.2020.06.019. Epub 2020 Jun 30.

Developments, application, and performance of artificial intelligence in dentistry - A systematic review

Sanjeev B Khanagar  1   2 , Ali Al-Ehaideb  1   2   3 , Prabhadevi C Maganur  4 , Satish Vishwanathaiah  4 , Shankargouda Patil  5 , Hosam A Baeshen  6 , Sachin C Sarode  7 , Shilpa Bhandi  8
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Free PMC article
Review

Developments, application, and performance of artificial intelligence in dentistry - A systematic review

Sanjeev B Khanagar et al. J Dent Sci. 2021 Jan.
Free PMC article

Abstract

Background/purpose: Artificial intelligence (AI) has made deep inroads into dentistry in the last few years. The aim of this systematic review was to identify the development of AI applications that are widely employed in dentistry and evaluate their performance in terms of diagnosis, clinical decision-making, and predicting the prognosis of the treatment.

Materials and methods: The literature for this paper was identified and selected by performing a thorough search in the electronic data bases like PubMed, Medline, Embase, Cochrane, Google scholar, Scopus, Web of science, and Saudi digital library published over the past two decades (January 2000-March 15, 2020).After applying inclusion and exclusion criteria, 43 articles were read in full and critically analyzed. Quality analysis was performed using QUADAS-2.

Results: AI technologies are widely implemented in a wide range of dentistry specialties. Most of the documented work is focused on AI models that rely on convolutional neural networks (CNNs) and artificial neural networks (ANNs). These AI models have been used in detection and diagnosis of dental caries, vertical root fractures, apical lesions, salivary gland diseases, maxillary sinusitis, maxillofacial cysts, cervical lymph nodes metastasis, osteoporosis, cancerous lesions, alveolar bone loss, predicting orthodontic extractions, need for orthodontic treatments, cephalometric analysis, age and gender determination.

Conclusion: These studies indicate that the performance of an AI based automated system is excellent. They mimic the precision and accuracy of trained specialists, in some studies it was found that these systems were even able to outmatch dental specialists in terms of performance and accuracy.

Keywords: Artificial intelligence dentistry; Artificial neural networks; Computer-aided diagnosis; Convolutional neural networks; Deep learning models; Machine learning.

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Figures

Fig. 1
Figure 1
Key aspects of artificial intelligence.
Fig. 2
Figure 2
Flow chart for screening and selection of articles.
Fig. 3
Figure 3
Trends of research on artificial intelligence in dentistry.
Fig. 4
Figure 4
Assessment of individual risk of bias domains.
Fig. 5
Figure 5
Concerns regarding applicability.
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