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An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19
Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating vira...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184329/ https://www.ncbi.nlm.nih.gov/pubmed/34194535 http://dx.doi.org/10.1155/2021/5528144 |
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author | Serena Low, Woan Ching Chuah, Joon Huang Tee, Clarence Augustine T. H. Anis, Shazia Shoaib, Muhammad Ali Faisal, Amir Khalil, Azira Lai, Khin Wee |
author_facet | Serena Low, Woan Ching Chuah, Joon Huang Tee, Clarence Augustine T. H. Anis, Shazia Shoaib, Muhammad Ali Faisal, Amir Khalil, Azira Lai, Khin Wee |
author_sort | Serena Low, Woan Ching |
collection | PubMed |
description | Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating viral pneumonia and COVID-19 disease using digital X-ray images. The current practices include tedious conventional processes that solely rely on the radiologist or medical consultant's technical expertise that are limited, time-consuming, inefficient, and outdated. The implementation is easily prone to human errors of being misdiagnosed. The development of deep learning and technology improvement allows medical scientists and researchers to venture into various neural networks and algorithms to develop applications, tools, and instruments that can further support medical radiologists. This paper presents an overview of deep learning techniques made in the chest radiography on COVID-19 and pneumonia cases. |
format | Online Article Text |
id | pubmed-8184329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-81843292021-06-29 An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19 Serena Low, Woan Ching Chuah, Joon Huang Tee, Clarence Augustine T. H. Anis, Shazia Shoaib, Muhammad Ali Faisal, Amir Khalil, Azira Lai, Khin Wee Comput Math Methods Med Review Article Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating viral pneumonia and COVID-19 disease using digital X-ray images. The current practices include tedious conventional processes that solely rely on the radiologist or medical consultant's technical expertise that are limited, time-consuming, inefficient, and outdated. The implementation is easily prone to human errors of being misdiagnosed. The development of deep learning and technology improvement allows medical scientists and researchers to venture into various neural networks and algorithms to develop applications, tools, and instruments that can further support medical radiologists. This paper presents an overview of deep learning techniques made in the chest radiography on COVID-19 and pneumonia cases. Hindawi 2021-06-04 /pmc/articles/PMC8184329/ /pubmed/34194535 http://dx.doi.org/10.1155/2021/5528144 Text en Copyright © 2021 Woan Ching Serena Low et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Serena Low, Woan Ching Chuah, Joon Huang Tee, Clarence Augustine T. H. Anis, Shazia Shoaib, Muhammad Ali Faisal, Amir Khalil, Azira Lai, Khin Wee An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19 |
title | An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19 |
title_full | An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19 |
title_fullStr | An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19 |
title_full_unstemmed | An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19 |
title_short | An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19 |
title_sort | overview of deep learning techniques on chest x-ray and ct scan identification of covid-19 |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184329/ https://www.ncbi.nlm.nih.gov/pubmed/34194535 http://dx.doi.org/10.1155/2021/5528144 |
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