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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM34211

Application of CNN Model on Medical Images (Chest X-Rays)

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM34211

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM34211

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

VB

Vrishabh Bansal

ML

Mehul Lahot

K

Kunal

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Abstract

Chest diseases encompass a range of conditions affecting the lungs, including infections caused by bacteria, viruses, or other microorganisms. These diseases can vary in severity, posing a potential threat to vulnerable individuals such as young children, older adults, and those with weakened immune systems. Detecting chest diseases involves employing diverse methods, such as physical examination, chest x-rays, blood tests, and sputum culture. During a physical examination, healthcare professionals utilize a stethoscope to listen for abnormal breathing sounds or crackling noises in the chest. They also assess factors like fever and respiratory rate. Chest x-rays provide a visual representation of the lungs, enabling the identification of areas displaying inflammation or fluid accumulation. Sputum culture involves collecting a sample of mucus expelled from the lungs through coughing and testing it for the presence of microorganisms.

KEYWORDS

Deep Learning CNN Chest X-Ray Images.

Cite This Article

Vrishabh Bansal, Mehul Lahot, Kunal, "Application of CNN Model on Medical Images (Chest X-Rays)," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024. https://doi.org/10.55041/IJSREM34211

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12/31/45430

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