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

Huqh MZU 1 , Abdullah JY 2 , Wong LS 3 , Jamayet NB 4 , Alam MK 5 , Rashid QF 6 Show all authors , Husein A 6 , Ahmad WMAW 7 , Eusufzai SZ 7 , Prasadh S 8 , Subramaniyan V 9 , Fuloria NK 10 , Fuloria S 10 , Sekar M 11 , Selvaraj S 12

Affiliations 

  • 1 Orthodontic Unit, School of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Malaysia
  • 2 Craniofacial Imaging Lab, School of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Malaysia
  • 3 Faculty of Health and Life Sciences, INTI International University, Nilai 71800, Malaysia
  • 4 Division of Clinical Dentistry (Prosthodontics), School of Dentistry, International Medical University, Bukit Jalil, Kuala Lumpur 57000, Malaysia
  • 5 Orthodontic Division, Preventive Dentistry Department, College of Dentistry, Jouf University, Sakaka 72345, Saudi Arabia
  • 6 Prosthodontic Unit, School of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Malaysia
  • 7 Department of Biostatistics, School of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Malaysia
  • 8 National Dental Center Singapore, 5 Second Hospital Avenue, Singapore 168938, Singapore
  • 9 Faculty of Medicine, Bioscience and Nursing, MAHSA University, Kuala Lumpur 42610, Malaysia
  • 10 Faculty of Pharmacy, AIMST University, Bedong 08100, Malaysia
  • 11 Department of Pharmaceutical Chemistry, Faculty of Pharmacy and Health Sciences, Royal College of Medicine Perak, Universiti Kuala Lumpur, Ipoh 30450, Malaysia
  • 12 Faculty of Dentistry, AIMST University, Bedong 08100, Malaysia
Int J Environ Res Public Health, 2022 Aug 31;19(17).
PMID: 36078576 DOI: 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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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