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Artificial intelligence applications in CBCT-based assessment of craniofacial airway volume and shape in sleep-disordered breathing: a systematic review.

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Bibliographic Details
Title: Artificial intelligence applications in CBCT-based assessment of craniofacial airway volume and shape in sleep-disordered breathing: a systematic review.
Authors: Al-Rawi NH; Oral & Craniofacial Health Sciences, University of Sharjah, Sharjah, United Arab Emirates., Elsayed W; Department of Basic Medical & Dental Sciences, College of Dentistry, Gulf Medical University, Ajman, United Arab Emirates.; Department of Oral Biology, College of Dentistry, Suez Canal University, Ismailia, Egypt., Al-Bayati SF; Diagnostic and Surgical Dental Sciences, College of Dentistry, Gulf Medical University, Ajman, United Arab Emirates., Saeed MH; Department of Clinical Sciences, College of Dentistry, Ajman University, Ajman, United Arab Emirates., Abdul Qader OAJ; College of Dentistry, Al-Mashreq University, Baghdad, Iraq., Shetty S; Oral & Craniofacial Health Sciences, University of Sharjah, Sharjah, United Arab Emirates., Uthman A; Diagnostic and Surgical Dental Sciences, College of Dentistry, Gulf Medical University, Ajman, United Arab Emirates.
Source: PeerJ [PeerJ] 2026 Jun 17; Vol. 14, pp. e21289. Date of Electronic Publication: 2026 Jun 17 (Print Publication: 2026).
Publication Type: Systematic Review; Journal Article
Journal Info: Publisher: PeerJ Inc Country of Publication: United States NLM ID: 101603425 Publication Model: eCollection Cited Medium: Internet ISSN: 2167-8359 (Electronic) Linking ISSN: 21678359 NLM ISO Abbreviation: PeerJ Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2167-8359
DOI:10.7717/peerj.21289