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Potential role of artificial intelligence in craniofacial surgery

The field of artificial intelligence (AI) is rapidly advancing, and AI models are increasingly applied in the medical field, especially in medical imaging, pathology, natural language processing, and biosignal analysis. On the basis of these advances, telemedicine, which allows people to receive med...

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Detalles Bibliográficos
Autores principales: Ryu, Jeong Yeop, Chung, Ho Yun, Choi, Kang Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Cleft Palate-Craniofacial Association 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8568494/
https://www.ncbi.nlm.nih.gov/pubmed/34732033
http://dx.doi.org/10.7181/acfs.2021.00507
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author Ryu, Jeong Yeop
Chung, Ho Yun
Choi, Kang Young
author_facet Ryu, Jeong Yeop
Chung, Ho Yun
Choi, Kang Young
author_sort Ryu, Jeong Yeop
collection PubMed
description The field of artificial intelligence (AI) is rapidly advancing, and AI models are increasingly applied in the medical field, especially in medical imaging, pathology, natural language processing, and biosignal analysis. On the basis of these advances, telemedicine, which allows people to receive medical services outside of hospitals or clinics, is also developing in many countries. The mechanisms of deep learning used in medical AI include convolutional neural networks, residual neural networks, and generative adversarial networks. Herein, we investigate the possibility of using these AI methods in the field of craniofacial surgery, with potential applications including craniofacial trauma, congenital anomalies, and cosmetic surgery.
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spelling pubmed-85684942021-11-18 Potential role of artificial intelligence in craniofacial surgery Ryu, Jeong Yeop Chung, Ho Yun Choi, Kang Young Arch Craniofac Surg Review Article The field of artificial intelligence (AI) is rapidly advancing, and AI models are increasingly applied in the medical field, especially in medical imaging, pathology, natural language processing, and biosignal analysis. On the basis of these advances, telemedicine, which allows people to receive medical services outside of hospitals or clinics, is also developing in many countries. The mechanisms of deep learning used in medical AI include convolutional neural networks, residual neural networks, and generative adversarial networks. Herein, we investigate the possibility of using these AI methods in the field of craniofacial surgery, with potential applications including craniofacial trauma, congenital anomalies, and cosmetic surgery. Korean Cleft Palate-Craniofacial Association 2021-10 2021-10-20 /pmc/articles/PMC8568494/ /pubmed/34732033 http://dx.doi.org/10.7181/acfs.2021.00507 Text en Copyright © 2021 The Korean Cleft Palate-Craniofacial Association https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Ryu, Jeong Yeop
Chung, Ho Yun
Choi, Kang Young
Potential role of artificial intelligence in craniofacial surgery
title Potential role of artificial intelligence in craniofacial surgery
title_full Potential role of artificial intelligence in craniofacial surgery
title_fullStr Potential role of artificial intelligence in craniofacial surgery
title_full_unstemmed Potential role of artificial intelligence in craniofacial surgery
title_short Potential role of artificial intelligence in craniofacial surgery
title_sort potential role of artificial intelligence in craniofacial surgery
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8568494/
https://www.ncbi.nlm.nih.gov/pubmed/34732033
http://dx.doi.org/10.7181/acfs.2021.00507
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