Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/30614| Title: | Clinical Applications of Artificial Intelligence and Machine Learning in Children with Cleft Lip and Palate—A Systematic Review |
| Authors: | Huqh, Mohamed Zahoor Ul Abdullah, Johari Yap Wong, Ling Shing Jamayet, Nafij Alam, Mohammad Khursheed Rashid, Qazi Farah Adam Husein Wan Muhamad Amir W. Ahmad Eusufzai, Sumaiya Zabin Prasadh, Somasundaram Subramaniyan, Vetriselvan Fuloria, Neeraj Kumar Fuloria, Shivkanya Sekar, Mahendran Selvaraj, Siddharthan (UniKL RCMP) |
| Keywords: | Artificial intelligence Cleft lip and palate Diagnostic performance Machine learning Treatment prediction |
| Issue Date: | Sep-2022 |
| Publisher: | MDPI |
| Citation: | Huqh, M. Z. U., Abdullah, J. Y., Wong, L. S., Jamayet, N., Alam, M. K., Rashid, Q. F., Adam Husein, Wan Muhamad Amir W. Ahmad, Eusufzai, S. Z., Prasadh, S., Subramaniyan, V., Fuloria, N. K., Fuloria, S., Sekar, M., & Selvaraj, S. (2022). Clinical Applications of Artificial Intelligence and Machine Learning in Children with Cleft Lip and Palate—A Systematic Review. International Journal of Environmental Research and Public Health, 19(17), 10860. https://doi.org/10.3390/ijerph191710860 |
| Abstract: | Objective: The objective of this systematic review was (a) to explore the current clinical applications of AI/ML (Artificial intelligence and Machine learning) techniques in diagnosis and treatment prediction in children with CLP (Cleft lip and palate), (b) to create a qualitative summary of results of the studies retrieved. Materials and methods: An electronic search was carried out using databases such as PubMed, Scopus, and the Web of Science Core Collection. Two reviewers searched the databases separately and concurrently. The initial search was conducted on 6 July 2021. The publishing period was unrestricted; however, the search was limited to articles involving human participants and published in English. Combinations of Medical Subject Headings (MeSH) phrases and free text terms were used as search keywords in each database. The following data was taken from the methods and results sections of the selected papers: The amount of AI training datasets utilized to train the intelligent system, as well as their conditional properties; Unilateral CLP, Bilateral CLP, Unilateral Cleft lip and alveolus, Unilateral cleft lip, Hypernasality, Dental characteristics, and sagittal jaw relationship in children with CLP are among the problems studied. Results: Based on the predefined search strings with accompanying database keywords, a total of 44 articles were found in Scopus, PubMed, and Web of Science search results. After reading the full articles, 12 papers were included for systematic analysis. Conclusions: Artificial intelligence provides an advanced technology that can be employed in AI-enabled computerized programming software for accurate landmark detection, rapid digital cephalometric analysis, clinical decision-making, and treatment prediction. In children with corrected unilateral cleft lip and palate, ML can help detect cephalometric predictors of future need for orthognathic surgery. |
| URI: | https://ir.unikl.edu.my/jspui/handle/123456789/30614 |
| ISSN: | 16617827 |
| Appears in Collections: | Journal Articles |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Clinical Applications of Artificial Intelligence and Machine Learning in Children with Cleft Lip and Palate—A Systematic Review.pdf | 690.26 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
Institutional Repository (UniKL IR)