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History and application of artificial neural networks in dentistry
Artificial intelligence (AI) is a commonly used term in daily life, and there are now two subconcepts that divide the entire range of meanings currently encompassed by the term. The coexistence of the concepts of strong and weak AI can be seen as a result of the recognition of the limits of mathemat...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178664/ https://www.ncbi.nlm.nih.gov/pubmed/30369809 http://dx.doi.org/10.4103/ejd.ejd_325_18 |
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author | Park, Wook Joo Park, Jun-Beom |
author_facet | Park, Wook Joo Park, Jun-Beom |
author_sort | Park, Wook Joo |
collection | PubMed |
description | Artificial intelligence (AI) is a commonly used term in daily life, and there are now two subconcepts that divide the entire range of meanings currently encompassed by the term. The coexistence of the concepts of strong and weak AI can be seen as a result of the recognition of the limits of mathematical and engineering concepts that have dominated the definition. This presentation reviewed the concept, history, and the current application of AI in daily life. Applications of AI are becoming a reality that is commonplace in all areas of modern human life. Efforts to develop robots controlled by AI have been continuously carried out to maximize human convenience. AI has also been applied in the medical decision-making process, and these AI systems can help nonspecialists to obtain expert-level information. Artificial neural networks are highly interconnected networks of computer processors inspired by biological nervous systems. These systems may help connect dental professionals all over the world. Currently, the use of AI is rapidly advancing beyond text-based, image-based dental practice. This presentation reviewed the history of artificial neural networks in the medical and dental fields, as well as current application in dentistry. As the use of AI in the entire medical field increases, the role of AI in dentistry will be greatly expanded. Currently, the use of AI is rapidly advancing beyond text-based, image-based dental practice. In addition to diagnosis of visually confirmed dental caries and impacted teeth, studies applying machine learning based on artificial neural networks to dental treatment through analysis of dental magnetic resonance imaging, computed tomography, and cephalometric radiography are actively underway, and some visible results are emerging at a rapid pace for commercialization. |
format | Online Article Text |
id | pubmed-6178664 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-61786642018-10-26 History and application of artificial neural networks in dentistry Park, Wook Joo Park, Jun-Beom Eur J Dent Review Article Artificial intelligence (AI) is a commonly used term in daily life, and there are now two subconcepts that divide the entire range of meanings currently encompassed by the term. The coexistence of the concepts of strong and weak AI can be seen as a result of the recognition of the limits of mathematical and engineering concepts that have dominated the definition. This presentation reviewed the concept, history, and the current application of AI in daily life. Applications of AI are becoming a reality that is commonplace in all areas of modern human life. Efforts to develop robots controlled by AI have been continuously carried out to maximize human convenience. AI has also been applied in the medical decision-making process, and these AI systems can help nonspecialists to obtain expert-level information. Artificial neural networks are highly interconnected networks of computer processors inspired by biological nervous systems. These systems may help connect dental professionals all over the world. Currently, the use of AI is rapidly advancing beyond text-based, image-based dental practice. This presentation reviewed the history of artificial neural networks in the medical and dental fields, as well as current application in dentistry. As the use of AI in the entire medical field increases, the role of AI in dentistry will be greatly expanded. Currently, the use of AI is rapidly advancing beyond text-based, image-based dental practice. In addition to diagnosis of visually confirmed dental caries and impacted teeth, studies applying machine learning based on artificial neural networks to dental treatment through analysis of dental magnetic resonance imaging, computed tomography, and cephalometric radiography are actively underway, and some visible results are emerging at a rapid pace for commercialization. Medknow Publications & Media Pvt Ltd 2018 /pmc/articles/PMC6178664/ /pubmed/30369809 http://dx.doi.org/10.4103/ejd.ejd_325_18 Text en Copyright: © 2018 European Journal of Dentistry http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Review Article Park, Wook Joo Park, Jun-Beom History and application of artificial neural networks in dentistry |
title | History and application of artificial neural networks in dentistry |
title_full | History and application of artificial neural networks in dentistry |
title_fullStr | History and application of artificial neural networks in dentistry |
title_full_unstemmed | History and application of artificial neural networks in dentistry |
title_short | History and application of artificial neural networks in dentistry |
title_sort | history and application of artificial neural networks in dentistry |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178664/ https://www.ncbi.nlm.nih.gov/pubmed/30369809 http://dx.doi.org/10.4103/ejd.ejd_325_18 |
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