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Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning
Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years. Many articles on deep learning have been published in radiologic journals. H...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Radiology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960318/ https://www.ncbi.nlm.nih.gov/pubmed/31920027 http://dx.doi.org/10.3348/kjr.2019.0312 |
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author | Do, Synho Song, Kyoung Doo Chung, Joo Won |
author_facet | Do, Synho Song, Kyoung Doo Chung, Joo Won |
author_sort | Do, Synho |
collection | PubMed |
description | Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years. Many articles on deep learning have been published in radiologic journals. However, radiologists may have difficulty in understanding and interpreting these studies because the study methods of deep learning differ from those of traditional radiology. This review article aims to explain the concepts and terms that are frequently used in deep learning radiology articles, facilitating general radiologists' understanding. |
format | Online Article Text |
id | pubmed-6960318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Korean Society of Radiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-69603182020-01-22 Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning Do, Synho Song, Kyoung Doo Chung, Joo Won Korean J Radiol Technology, Experiment, and Physics Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years. Many articles on deep learning have been published in radiologic journals. However, radiologists may have difficulty in understanding and interpreting these studies because the study methods of deep learning differ from those of traditional radiology. This review article aims to explain the concepts and terms that are frequently used in deep learning radiology articles, facilitating general radiologists' understanding. The Korean Society of Radiology 2020-01 2019-12-06 /pmc/articles/PMC6960318/ /pubmed/31920027 http://dx.doi.org/10.3348/kjr.2019.0312 Text en Copyright © 2020 The Korean Society of Radiology http://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/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technology, Experiment, and Physics Do, Synho Song, Kyoung Doo Chung, Joo Won Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning |
title | Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning |
title_full | Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning |
title_fullStr | Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning |
title_full_unstemmed | Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning |
title_short | Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning |
title_sort | basics of deep learning: a radiologist's guide to understanding published radiology articles on deep learning |
topic | Technology, Experiment, and Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960318/ https://www.ncbi.nlm.nih.gov/pubmed/31920027 http://dx.doi.org/10.3348/kjr.2019.0312 |
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