UGC Approved Journal no 63975(19)

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Published in:

Volume 10 Issue 4
April-2023
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2304B27


Registration ID:
513646

Page Number

l159-l162

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Title

PNEUMONIA DETECTION USING VARIOUS NEURAL NETWORK ALGORITHMS

Abstract

Abstract—The term Pneumonia refers to a type of infection that increases the alveoli sacs in lungs. There are various types of bacteria can cause pneumonia. Streptococcus pneumoniae is one of the most common bacteria. Viruses that contaminate our lungs and airways can cause pneumonia. Influenza virus and rhinovirus are the most common viruses that causes viral pneumonia for people above age group of 20. Fungi such as Pneumocystis jirovecii is liable to cause pneumonia, particularly for people who have weak immune systems. When a person is suffering from bronchopneumonia, then air sacs are occupied with fluid and pus, which makes inhaling and exhaling painful also limits the oxygen intake. These kinds of infections usually spread when infected people come in direct contact with normal people. People with prior health issues and adult above age group of 65 are at higher risk of getting infected. There are several imaging modalities that can be applied for the detection of pneumonia in hospitals and clinics which includes computed tomography, chest radiography, magnetic resonance imagingetc. Chest radiography is one of the most used methods for detecting pneumonia worldwide due to its lower cost and they are easily accessible. Chest radiographs is challenging for detecting pneumonia even though it provides significant amount of information about a patient’s condition,because images have similar opaqueness when compared with images of other lung defects such as lung cancer, and excess fluid which leads to uncertainty.

Key Words

CNN; Chest X-Ray; Feature Extraction; organizing map algorithm; Pneumonia Detection

Cite This Article

"PNEUMONIA DETECTION USING VARIOUS NEURAL NETWORK ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.l159-l162, April-2023, Available :http://www.jetir.org/papers/JETIR2304B27.pdf

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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

"PNEUMONIA DETECTION USING VARIOUS NEURAL NETWORK ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppl159-l162, April-2023, Available at : http://www.jetir.org/papers/JETIR2304B27.pdf

Publication Details

Published Paper ID: JETIR2304B27
Registration ID: 513646
Published In: Volume 10 | Issue 4 | Year April-2023
DOI (Digital Object Identifier):
Page No: l159-l162
Country: Bangalore, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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