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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM27783

Covid 19 Detection Using Deep Learning and Covid 19 Symptoms Checker

Stream/Area:

-

Subject:

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Paper ID:

10.55041/IJSREM27783

Volume:

7 |

12 |

Dec 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

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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D

Dr.K.Kalaiselvi

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Abstract

The goal of this project is to classify healthy individuals, COVID-19 cases, and viral pneumonia cases. Deep learning is a type of machine learning. It enables us to teach artificial intelligence to anticipate outcomes given a set of data.Artificial intelligence can be trained through supervised learning. Voice and facial recognition, disease diagnosis, defence, and security are all domains where deep learning is applied. Artificial neural networks are represented by the word deep in deep learning. The human brain inspired artificial neural networks. It is made up of neurons, just like the human brain. The amount and speed of learning are the main differences between them. To put it another way, artificial neural networks require data and processing capacity to be trained. The quality of machine learning methods is determined by the algorithms used.

KEYWORDS

COVID-19 Privacy Preserved Data Sharing deep learning Symptoms checker

Cite This Article

Dr.K.Kalaiselvi, "Covid 19 Detection Using Deep Learning and Covid 19 Symptoms Checker," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 12, Dec 2023. https://doi.org/10.55041/IJSREM27783

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Publication Date

12/29/2023

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