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- Title
Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review.
- Authors
Junaid, Nuha; Khan, Niha; Ahmed, Naseer; Abbasi, Maria Shakoor; Das, Gotam; Maqsood, Afsheen; Ahmed, Abdul Razzaq; Marya, Anand; Alam, Mohammad Khursheed; Heboyan, Artak
- Abstract
This study aimed to analyze the existing literature on how artificial intelligence is being used to support the identification of cephalometric landmarks. The systematic analysis of literature was carried out by performing an extensive search in PubMed/MEDLINE, Google Scholar, Cochrane, Scopus, and Science Direct databases. Articles published in the last ten years were selected after applying the inclusion and exclusion criteria. A total of 17 full-text articles were systematically appraised. The Cochrane Handbook for Systematic Reviews of Interventions (CHSRI) and Newcastle-Ottawa quality assessment scale (NOS) were adopted for quality analysis of the included studies. The artificial intelligence systems were mainly based on deep learning-based convolutional neural networks (CNNs) in the included studies. The majority of the studies proposed that AI-based automatic cephalometric analyses provide clinically acceptable diagnostic performance. They have worked remarkably well, with accuracy and precision similar to the trained orthodontist. Moreover, they can simplify cephalometric analysis and provide a quick outcome in practice. Therefore, they are of great benefit to orthodontists, as with these systems they can perform tasks more efficiently.
- Subjects
DENTAL pathology; ONLINE information services; MEDICAL databases; DEEP learning; PREDICTIVE tests; RESEARCH evaluation; SYSTEMATIC reviews; ARTIFICIAL intelligence; ORTHODONTICS; CEPHALOMETRY; RESEARCH funding; COMPUTER-aided diagnosis; MEDLINE; ARTIFICIAL neural networks
- Publication
Healthcare (2227-9032), 2022, Vol 10, Issue 12, p2454
- ISSN
2227-9032
- Publication type
Article
- DOI
10.3390/healthcare10122454