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Current Applications of Artificial Intelligence in Cleft Care: A Scoping Review
- Source :
- Frontiers in Medicine, Vol 8 (2021)
- Publication Year :
- 2021
- Publisher :
- Frontiers Media S.A., 2021.
-
Abstract
- Objective: This scoping review aims to identify the various areas and current status of the application of artificial intelligence (AI) for aiding individuals with cleft lip and/or palate.Introduction: Cleft lip and/or palate contributes significantly toward the global burden on the healthcare system. Artificial intelligence is a technology that can help individuals with cleft lip and/or palate, especially those in areas with limited access to receive adequate care.Inclusion Criteria: Studies that used artificial intelligence to aid the diagnosis, treatment, or its planning in individuals with cleft lip and/or palate were included.Methodology: A search of the Pubmed, Embase, and IEEE Xplore databases was conducted using search terms artificial intelligence and cleft lip and/or palate. Gray literature was searched using Google Scholar. The study was conducted according to the PRISMA- ScR guidelines.Results: The initial search identified 458 results, which were screened based on title and abstracts. After the screening, removal of duplicates, and a full-text reading of selected articles, 26 publications were included. They explored the use of AI in cleft lip and/or palate to aid in decisions regarding diagnosis, treatment, especially speech therapy, and prediction.Conclusion: There is active interest and immense potential for the use of artificial intelligence in cleft lip and/or palate. Most studies currently focus on speech in cleft palate. Multi-center studies that include different populations, with collaboration amongst academicians and researchers, can further develop the technology.
Details
- Language :
- English
- ISSN :
- 2296858X
- Volume :
- 8
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Medicine
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.20167f2669584d1cbeb66432b70b6e0b
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fmed.2021.676490