UGC Approved Journal no 63975(19)

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

Volume 10 Issue 5
May-2023
eISSN: 2349-5162

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

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2305B94


Registration ID:
517569

Page Number

l691-l697

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Title

Pneumonia Detection using Convolutional Neural Network (CNN)

Abstract

This paper explores the application of Convolutional Neural Networks (CNNs) for pneumonia detection using chest X-ray images. The CNN model achieved an accuracy of 96.00% in detecting pneumonia and distinguishing between different pneumonia types. These results suggest that CNN-based approaches have the potential to improve the efficiency and accuracy of pneumonia diagnosis, aiding healthcare professionals in making informed decisions. Further research and validation are needed to assess the real-world clinical utility of this CNN-based approach.

Key Words

Pneumonia , Convolutional Neural Network

Cite This Article

"Pneumonia Detection using Convolutional Neural Network (CNN)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.l691-l697, May-2023, Available :http://www.jetir.org/papers/JETIR2305B94.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

"Pneumonia Detection using Convolutional Neural Network (CNN)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppl691-l697, May-2023, Available at : http://www.jetir.org/papers/JETIR2305B94.pdf

Publication Details

Published Paper ID: JETIR2305B94
Registration ID: 517569
Published In: Volume 10 | Issue 5 | Year May-2023
DOI (Digital Object Identifier):
Page No: l691-l697
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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