Deep learning for tooth identification and numbering on dental radiography: a systematic review and meta-analysis.

ABSTRACT:

Objectives

Improved tools based on deep learning can be used to accurately number and identify teeth. This study aims to review the use of deep learning in tooth numbering and identification.

Methods

An electronic search was performed through October 2023 on PubMed, Scopus, Cochrane, Google Scholar, IEEE, arXiv, and medRxiv. Studies that used deep learning models with segmentation, object detection, or classification tasks for teeth identification and numbering of human dental radiographs were included. For risk of bias assessment, included studies were critically analysed using quality assessment of diagnostic accuracy studies (QUADAS-2). To generate plots for meta-analysis, MetaDiSc and STATA 17 (StataCorp LP, College Station, TX, USA) were used. Pooled outcome diagnostic

SUBMITTER: Sadr S 

PROVIDER: S-EPMC11003608 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature