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Clinical Applications of Artificial Intelligence and Machine Learning in Children with Cleft Lip and Palate—A Systematic Review

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dc.contributor.author Huqh, Mohamed Zahoor Ul
dc.contributor.author Abdullah, Johari Yap
dc.contributor.author Wong, Ling Shing
dc.contributor.author Jamayet, Nafij
dc.contributor.author Alam, Mohammad Khursheed
dc.contributor.author Rashid, Qazi Farah
dc.contributor.author Adam Husein
dc.contributor.author Wan Muhamad Amir W. Ahmad
dc.contributor.author Eusufzai, Sumaiya Zabin
dc.contributor.author Prasadh, Somasundaram
dc.contributor.author Subramaniyan, Vetriselvan
dc.contributor.author Fuloria, Neeraj Kumar
dc.contributor.author Fuloria, Shivkanya
dc.contributor.author Sekar, Mahendran
dc.contributor.author Selvaraj, Siddharthan
dc.contributor.author (UniKL RCMP)
dc.date.accessioned 2024-06-25T02:53:06Z
dc.date.available 2024-06-25T02:53:06Z
dc.date.issued 2022-09
dc.identifier.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 en_US
dc.identifier.issn 16617827
dc.identifier.uri https://ir.unikl.edu.my/jspui/handle/123456789/30614
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher MDPI en_US
dc.subject Artificial intelligence en_US
dc.subject Cleft lip and palate en_US
dc.subject Diagnostic performance en_US
dc.subject Machine learning en_US
dc.subject Treatment prediction en_US
dc.title Clinical Applications of Artificial Intelligence and Machine Learning in Children with Cleft Lip and Palate—A Systematic Review en_US
dc.type Article en_US


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