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Smart access development for classifying lung disease with chest x-ray images using deep learning
Recently the world has come across a pandemic disease known as covid-19. The presence of symptoms of covid-19 and pneumonia may be alike to other types of lung illnesses. So, because of this, it is difficult for the affected person or medical experts to identify the condition. Chest x-ray provides g...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049837/ https://www.ncbi.nlm.nih.gov/pubmed/33880332 http://dx.doi.org/10.1016/j.matpr.2021.03.650 |
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author | kumaraguru, Tarunika Abirami, P. Darshan, K.M. Angeline Kirubha, S.P. Latha, S. Muthu, P. |
author_facet | kumaraguru, Tarunika Abirami, P. Darshan, K.M. Angeline Kirubha, S.P. Latha, S. Muthu, P. |
author_sort | kumaraguru, Tarunika |
collection | PubMed |
description | Recently the world has come across a pandemic disease known as covid-19. The presence of symptoms of covid-19 and pneumonia may be alike to other types of lung illnesses. So, because of this, it is difficult for the affected person or medical experts to identify the condition. Chest x-ray provides general orientation which can be an initial investigative study in the analysis of lung diseases. Information from retenogram studies help the finding of covid-19 and pneumonia affecting the lungs. We use a Convolution Neural Network (CNN) in Tensor Flow and Keras based covid-19, pneumonia classification. The best fit model of CNN is then deployed in the Django framework for providing a better user interface and predicting the output. |
format | Online Article Text |
id | pubmed-8049837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80498372021-04-16 Smart access development for classifying lung disease with chest x-ray images using deep learning kumaraguru, Tarunika Abirami, P. Darshan, K.M. Angeline Kirubha, S.P. Latha, S. Muthu, P. Mater Today Proc Article Recently the world has come across a pandemic disease known as covid-19. The presence of symptoms of covid-19 and pneumonia may be alike to other types of lung illnesses. So, because of this, it is difficult for the affected person or medical experts to identify the condition. Chest x-ray provides general orientation which can be an initial investigative study in the analysis of lung diseases. Information from retenogram studies help the finding of covid-19 and pneumonia affecting the lungs. We use a Convolution Neural Network (CNN) in Tensor Flow and Keras based covid-19, pneumonia classification. The best fit model of CNN is then deployed in the Django framework for providing a better user interface and predicting the output. Elsevier Ltd. 2021 2021-04-16 /pmc/articles/PMC8049837/ /pubmed/33880332 http://dx.doi.org/10.1016/j.matpr.2021.03.650 Text en © 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 12th National Conference on Recent Advancements in Biomedical Engineering. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article kumaraguru, Tarunika Abirami, P. Darshan, K.M. Angeline Kirubha, S.P. Latha, S. Muthu, P. Smart access development for classifying lung disease with chest x-ray images using deep learning |
title | Smart access development for classifying lung disease with chest x-ray images using deep learning |
title_full | Smart access development for classifying lung disease with chest x-ray images using deep learning |
title_fullStr | Smart access development for classifying lung disease with chest x-ray images using deep learning |
title_full_unstemmed | Smart access development for classifying lung disease with chest x-ray images using deep learning |
title_short | Smart access development for classifying lung disease with chest x-ray images using deep learning |
title_sort | smart access development for classifying lung disease with chest x-ray images using deep learning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049837/ https://www.ncbi.nlm.nih.gov/pubmed/33880332 http://dx.doi.org/10.1016/j.matpr.2021.03.650 |
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