Current Applications of Artificial Intelligence in Cleft Care: A Scoping Review

Dhillon, Harnoor; Chaudhari, Prabhat Kumar; Dhingra, Kunaal; Kuo, Rong-Fu; Sokhi, Ramandeep Kaur; Alam, Mohammad Khursheed; Ahmad, Shandar

doi:10.3389/fmed.2021.676490

Cited by 19 publications

(9 citation statements)

References 55 publications

(104 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although CLP is a common birth deformity, its prevalence differs among various ethnic origin. The greater prevalence of clefts among Asians compared to other ethnic groups suggests two probable reasons for the substantial research in China: the need to address a potential problem and the availability of data [ 54 , 55 ].…”

Section: Discussionmentioning

confidence: 99%

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

Huqh

Abdullah

Wong

et al. 2022

IJERPH

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

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

Huqh

Abdullah

Wong

et al. 2022

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…CNN algorithms were demonstrated to be a suitable tool for the automatically detecting cancers (73, 78). It is worth mentioning that AI also plays a role in managing cleft lip and palate in risk prediction, diagnosis, pre-surgical orthopaedics, speech assessment, and surgery (79).…”

Section: Ai In Oral and Maxillofacial Pathologymentioning

confidence: 99%

Artificial intelligence in dentistry—A review

Ding

Zhao

et al. 2023

Front. Dent. Med

View full text Add to dashboard Cite

Artificial Intelligence (AI) is the ability of machines to perform tasks that normally require human intelligence. AI is not a new term, the concept of AI can be dated back to 1950. However, it has not become a practical tool until two decades ago. Owing to the rapid development of three cornerstones of current AI technology—big data (coming through digital devices), computational power, and AI algorithm—in the past two decades, AI applications have been started to provide convenience to people's lives. In dentistry, AI has been adopted in all dental disciplines, i.e., operative dentistry, periodontics, orthodontics, oral and maxillofacial surgery, and prosthodontics. The majority of the AI applications in dentistry go to the diagnosis based on radiographic or optical images, while other tasks are not as applicable as image-based tasks mainly due to the constraints of data availability, data uniformity, and computational power for handling 3D data. Evidence-based dentistry (EBD) is regarded as the gold standard for the decision-making of dental professionals, while AI machine learning (ML) models learn from human expertise. ML can be seen as another valuable tool to assist dental professionals in multiple stages of clinical cases. This review narrated the history and classification of AI, summarised AI applications in dentistry, discussed the relationship between EBD and ML, and aimed to help dental professionals to understand AI as a tool better to assist their routine work with improved efficiency.

show abstract

“…53 Investigations using family history, genetic analysis, and toxicology data have demonstrated population-specific applications for assessing developmental risk. 30 32 53 54 The application of convolutional neural networks for image recognition has shown promise in identifying clefts by ultrasound imaging. 55 While still in early stages, these developments offer cost-effective avenues for classifying risk and augmenting existing diagnostic tools.…”

Section: Introductionmentioning

confidence: 99%

Updates in Cleft Care

Parham,

Simpson,

Moreno

et al. 2023

Semin Plast Surg

View full text Add to dashboard Cite

Cleft lip and/or palate is a congenital malformation with a wide range of presentations, and its effective treatment necessitates sustained, comprehensive care across an affected child's life. Early diagnosis, ideally through prenatal imaging or immediately postbirth, is paramount. Access to longitudinal care and long-term follow-up with a multidisciplinary approach, led by the recommendations of the American Cleft Palate Association, is the best way to ensure optimal outcomes. Multiple specialties including plastic surgery, otolaryngology, speech therapy, orthodontists, psychologists, and audiologists all may be indicated in the care of the child. Primary repair of the lip, nose, and palate are generally conducted during infancy. Postoperative care demands meticulous oversight to detect potential complications. If necessary, revisional surgeries should be performed before the child begin primary school. As the child matures, secondary procedures like alveolar bone grafting and orthognathic surgery may be requisite. The landscape of cleft care has undergone significant transformation since early surgical correction, with treatment plans now tailored to the specific type and severity of the cleft. The purpose of this text is to outline the current standards of care in children born with cleft lip and/or palate and to highlight ongoing advancements in the field.

show abstract

Current Applications of Artificial Intelligence in Cleft Care: A Scoping Review

Cited by 19 publications

References 55 publications

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

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

Artificial intelligence in dentistry—A review

Updates in Cleft Care

Contact Info

Product

Resources

About