Performance of artificial intelligence on cervical vertebral maturation assessment: a systematic review and meta-analysis.

ABSTRACT:

Background

Artificial intelligence (AI) methods, including machine learning and deep learning, are increasingly applied in orthodontics for tasks like assessing skeletal maturity. Accurate timing of treatment is crucial, but traditional methods such as cervical vertebral maturation (CVM) staging have limitations due to observer variability and complexity. AI has the potential to automate CVM assessment, enhancing reliability and user-friendliness. This systematic review and meta-analysis aimed to evaluate the overall performance of artificial intelligence (AI) models in assessing cervical vertebrae maturation (CVM) in radiographs, when compared to clinicians.

Methods

Electronic databases of Medline (via PubMed), Google Scholar, Scopus, Embase, IEEE ArXiv and MedRxiv were sea

SUBMITTER: Sadeghi TS 

PROVIDER: S-EPMC11796225 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature