Book chapter
Application of artificial intelligence in treating patients with cleft and craniofacial anomalies
Cleft and Craniofacial Orthodontics, pp.638-646
John Wiley & Sons, Inc
03/10/2023
DOI: 10.1002/9781119778387.ch48
Abstract
Deep learning (DL) is the most recent subset of machine learning with networks capable of learning unsupervised from unstructured data. This chapter provides a comprehensive review of the current application of artificial intelligence in treating patients with clefts and craniofacial anomalies (CFAs). AI can be used in the detection and classification of CFAs, identifying facial phenotypes of genetic disorders with DL, analysis of CFAs, and prediction of genetic risk of non‐syndromic oral clefts. Benign metopic ridge (BMR) is a normal variant of metopic suture, which is present in 10‐25% of infants. Patients with BMR are recommended for conservative non‐surgical treatment, while those with true metopic craniosynostosis require surgical correction. Cephalometric analysis is typically time‐consuming and needs to be performed by a well‐trained expert. Cone‐beam computed tomography is rapidly supplanting 2D cephalometric analysis in craniofacial care due to its value in 3D diagnosis and virtual treatment planning.
Details
- Title: Subtitle
- Application of artificial intelligence in treating patients with cleft and craniofacial anomalies
- Creators
- Mohammed H ElnagarSumit YadavFlavio SanchezShankar Rengasamy VenugopalanVeerasathpurush Allareddy
- Contributors
- Pradip R Shetye (Editor)Travis L Gibson (Editor)
- Resource Type
- Book chapter
- Publication Details
- Cleft and Craniofacial Orthodontics, pp.638-646
- Publisher
- John Wiley & Sons, Inc; Hoboken, NJ, USA
- DOI
- 10.1002/9781119778387.ch48
- Number of pages
- 9
- Language
- English
- Date published
- 03/10/2023
- Academic Unit
- Orthodontics
- Record Identifier
- 9984367580702771
Metrics
45 Record Views