UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 4
April-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Unique Identifier

Published Paper ID:
JETIRES06027


Registration ID:
307457

Page Number

120-126

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Title

DIAGNOSIS OF PNEUMONIA FROM X-RAYS USING DEEP LEARNING

Abstract

Pneumonia is an infection that inflames the air sacs in one or both lungs. The air sacs may fill with fluid or pus (purulent material), causing cough with phlegm or pus, fever, chills, and difficulty breathing. A variety of organisms, including bacteria, viruses and fungi, can cause pneumonia. It is an infection of the lungs with a range of possible causes. It can be a serious and life-threatening disease. It normally starts with a bacterial, viral, or fungal infection. The lungs become inflamed, and the tiny air sacs, or alveoli, inside the lungs fill up with fluid. Over 150 million people get infected with pneumonia on an annual basis especially children under 5 years old. COVID-19 pneumonia is a serious illness that can be deadly. Early detection of Pneumonia and COVID-19 is crucial in reducing mortality. The rich collection of annotated datasets piloted the robustness of deep learning techniques to effectuate the implementation of diverse medical imaging tasks. This proposed system involves detection of Pneumonia and COVID-19 based on deep learning which is proposed for thoracic X-Ray images.

Key Words

Pneumonia, X-rays, Convolutional neural network, deep learning.

Cite This Article

"DIAGNOSIS OF PNEUMONIA FROM X-RAYS USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.120-126, April-2021, Available :http://www.jetir.org/papers/JETIRES06027.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"DIAGNOSIS OF PNEUMONIA FROM X-RAYS USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp120-126, April-2021, Available at : http://www.jetir.org/papers/JETIRES06027.pdf

Publication Details

Published Paper ID: JETIRES06027
Registration ID: 307457
Published In: Volume 8 | Issue 4 | Year April-2021
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.26855
Page No: 120-126
Country: CHENNAI, Tamilnadu, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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