UGC Approved Journal no 63975(19)

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

Volume 9 Issue 2
February-2022
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2202484


Registration ID:
320850

Page Number

e654-e667

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Title

COVID 19 : DIAGNOSIS AND TREATMENT USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING MODELS

Abstract

The COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long /Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Artificial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications.

Key Words

COVID19,Deep Learning, Long Short Term Memory(LSTM),Extreme Learning Machine(ELM),Artificial Neural Network(ANN)

Cite This Article

"COVID 19 : DIAGNOSIS AND TREATMENT USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING MODELS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 2, page no.e654-e667, February-2022, Available :http://www.jetir.org/papers/JETIR2202484.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

"COVID 19 : DIAGNOSIS AND TREATMENT USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING MODELS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 2, page no. ppe654-e667, February-2022, Available at : http://www.jetir.org/papers/JETIR2202484.pdf

Publication Details

Published Paper ID: JETIR2202484
Registration ID: 320850
Published In: Volume 9 | Issue 2 | Year February-2022
DOI (Digital Object Identifier):
Page No: e654-e667
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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