Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review.

ABSTRACT:

Background

The aim of this systematic review is to evaluate the diagnostic performance of Artificial Intelligence (AI) models designed for the detection of caries lesion (CL).

Materials and methods

An electronic literature search was conducted on PubMed, Web of Science, SCOPUS, LILACS and Embase databases for retrospective, prospective and cross-sectional studies published until January 2023, using the following keywords: artificial intelligence (AI), machine learning (ML), deep learning (DL), artificial neural networks (ANN), convolutional neural networks (CNN), deep convolutional neural networks (DCNN), radiology, detection, diagnosis and dental caries (DC). The quality assessment was performed using the guidelines of QUADAS-2.

Results

Twenty articles that met the s

SUBMITTER: Albano D 

PROVIDER: S-EPMC10894487 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature