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Prevalence of Machine Learning in Craniofacial Surgery
- Source :
- Journal of Craniofacial Surgery. 31:898-903
- Publication Year :
- 2020
- Publisher :
- Ovid Technologies (Wolters Kluwer Health), 2020.
-
Abstract
- Machine learning (ML) revolves around the concept of using experience to teach computer-based programs to reliably perform specific tasks. Healthcare setting is an ideal environment for adaptation of ML applications given the multiple specific tasks that could be allocated to computer programs to perform. There have been several scoping reviews published in literature looking at the general acceptance and adaptability of surgical specialities to ML applications, but very few focusing on the application towards craniofacial surgery. This study aims to present a detailed scoping review regarding the use of ML applications in craniofacial surgery.
- Subjects :
- media_common.quotation_subject
Machine learning
computer.software_genre
Adaptability
Machine Learning
03 medical and health sciences
0302 clinical medicine
Health care
Prevalence
Humans
Medicine
030223 otorhinolaryngology
Adaptation (computer science)
Craniofacial surgery
media_common
Ideal (set theory)
business.industry
Skull
030206 dentistry
General Medicine
Otorhinolaryngology
Bibliometrics
Face
Surgery
Artificial intelligence
business
Delivery of Health Care
computer
Subjects
Details
- ISSN :
- 10492275
- Volume :
- 31
- Database :
- OpenAIRE
- Journal :
- Journal of Craniofacial Surgery
- Accession number :
- edsair.doi.dedup.....d6d6b9bfbfedc1615cd4e3d7b91fcc74