UGC Approved Journal no 63975(19)

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

Volume 9 Issue 9
September-2022
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2209238


Registration ID:
501219

Page Number

c160-c166

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Title

Artificial Intelligence Based Covid 19 Detection

Abstract

In this paper, we have prepared a few profound convolutional networks with presented preparing strategies for arranging X-beam pictures into three classes: typical, pneumonia, and COVID-19, in view of two open-source datasets. Concentrates on COVID-19 have shown that more established grown-ups and individuals with a background marked by different clinical issues, explicitly earlier instances of pneumonia, are at a higher gamble of creating extreme difficulties from COVID-19. As pneumonia is a typical kind of contamination that spreads in the lungs, specialists as a rule perform chest X-beam to distinguish the tainted areas of the lungs. In this reserach, Artificial Intelligences are used to perform one-hot encoding on the labelled chest X-ray images and transform them into categorical form using Python’s to categorical tool. Subsequently, various deep learning features such as convolutional neural network (CNN), CONV2D, MaxPooling2D, dropout, flatten, L1-regularization dense, and input are used to build a detection model. Adam is used as an optimizer, which can be further applied to predict pneumonia in COVID-19 patients. The model predicted pneumonia with an average accuracy of 99.45%, sensitivity of 95.92%, and specificity of 100%. &e model also efficiently reduces training loss and increases accuracy.

Key Words

COVID-19, Neural network, Convolutional neural network, Deep learning, Medical image analysis

Cite This Article

"Artificial Intelligence Based Covid 19 Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.c160-c166, September-2022, Available :http://www.jetir.org/papers/JETIR2209238.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

"Artificial Intelligence Based Covid 19 Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppc160-c166, September-2022, Available at : http://www.jetir.org/papers/JETIR2209238.pdf

Publication Details

Published Paper ID: JETIR2209238
Registration ID: 501219
Published In: Volume 9 | Issue 9 | Year September-2022
DOI (Digital Object Identifier):
Page No: c160-c166
Country: Bangalore/Kolar, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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