Clinical Applications F Artificial Intelligence in Dental and Maxillofacial Radiology among Children: A Systematic Review and Meta-Analysis

Abstract

Background and aim: artificial intelligence (AI) has evolved from the concept of strong AI, which imitates human
intelligence, to the implementation of weak AI that can solve certain problems. At the moment evidence of AI used in
DMFR / diagnostic imaging in children has not been assessed Therefore the aim of this systematic review and metaanalysis was Clinical applications of artificial intelligence in DMFR.
Methods: MEDLINE, PubMed, Cochrane Library, Embase, ISI, Google scholar were used as electronic databases to
perform a systematic literature until 2019. A commercially available software program (Endnote X9) was used for
electronic title management. Searches were performed with keywords, “artificial intelligence OR AI”, “dental OR
maxillofacial OR dental and maxillofacial radiology OR DMFR”, “CBCT”,” Cephalometric OR radiographs”
Results A total of 1862 potentially relevant titles and abstracts were found during the electronic and manual search.
Finally, a total of five publications fulfilled the inclusion criteria required for this systematic review. In these review, four
stiduies use Cephalometric radiographs and only one study use CBCT. With regard to the applications of these AI models,
one reported on localization/measurement of cephalometric landmarks.
Conclusions: AI models for DMFR were mainly focusing on automated localization of cephalometric landmarks