Covid diseases analysis using chest x-ray with machine learning approach.

March 2022
Vol-8, Issue-2
Paper ID: 16183
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
computer engineering
Keywords
ML COVID-19 Modeling Forecasting.
Abstract
The COVID-19 epidemic has forced several organizations to undergo major shift, to examine essential aspects of their economic cycles and to make use of invention in order to maintain activities whilst maintaining a shifting rule scene and unique method. This review provides a comprehensive understanding via a framework of facts and an original approach of huge no of key issues and fundamental subtleties impacting organizations and society fromCOVID-19. The views for different welcoming industry professionals are analyzed and broken down when the specific interpretations may be understood: Web learning, modern technology, manmade brainpower, data board, social communication, security of networks, information giant, block chain, security, multifaceted invention and approach from the present emergency standpoint and influence on such specific areas. The master perspectives give the extent of the elements optimum comprehension, distinguishing central questions and proposals for hypothesis and practice by utilizing chest X-Ray pictures with ML approach. In the paper, the use of these ML methods to cope with the COVID-19 pandemic flow situation is a promising aspect, just as the prevention of Covid infection model is proposed. Result shows the proposed hybrid approach gives better accuracy as compare to other.

Author Information

# Name Institute / Affiliation
1 Ms. Manisha S. Kharat Sharadchandra Pawar college of engineering and technology,someshwarnagar
2 Mrs.Prof. Mangal .V. Wagh Sharadchandra Pawar college of engineering and technology,someshwarnagar
3 Ms. Priyanka S. Pingale Sharadchandra Pawar college of engineering and technology,someshwarnagar
4 Ms. Monali B. Patole Sharadchandra Pawar college of engineering and technology,someshwarnagar
5 Ms. Priya S. Lonkar Sharadchandra Pawar college of engineering and technology,someshwarnagar

How to Cite

Use the following formats to cite this article in your research.

APA Style
Kharat, Ms. Manisha S., Wagh, Mrs.Prof. Mangal .V., Pingale, Ms. Priyanka S., Patole, Ms. Monali B., & Lonkar, Ms. Priya S. (2022). Covid diseases analysis using chest x-ray with machine learning approach.. International Journal of Advance Research and Innovative Ideas In Education, 8(2), 520-523.
MLA Style
Kharat, Ms. Manisha S., et al. "Covid diseases analysis using chest x-ray with machine learning approach.." International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 2, 2022, pp. 520-523.
IEEE Style
Ms. Manisha S. Kharat, Mrs.Prof. Mangal .V. Wagh, Ms. Priyanka S. Pingale, Ms. Monali B. Patole, and Ms. Priya S. Lonkar, "Covid diseases analysis using chest x-ray with machine learning approach.," International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 2, pp. 520-523, 2022.
Vancouver Style
Kharat Ms. Manisha S., Wagh Mrs.Prof. Mangal .V., Pingale Ms. Priyanka S., Patole Ms. Monali B., Lonkar Ms. Priya S.. Covid diseases analysis using chest x-ray with machine learning approach.. International Journal of Advance Research and Innovative Ideas In Education. 2022;8(2):520-523.
Harvard Style
Kharat, Ms. Manisha S., Wagh, Mrs.Prof. Mangal .V., Pingale, Ms. Priyanka S., Patole, Ms. Monali B., & Lonkar, Ms. Priya S. (2022) 'Covid diseases analysis using chest x-ray with machine learning approach.', International Journal of Advance Research and Innovative Ideas In Education, 8(2), pp. 520-523.
Chicago Style
Kharat, Ms. Manisha S., et al. "Covid diseases analysis using chest x-ray with machine learning approach.." International Journal of Advance Research and Innovative Ideas In Education 8, no. 2 (2022): 520-523.
Turabian Style
Kharat, Ms. Manisha S., et al. "Covid diseases analysis using chest x-ray with machine learning approach.." International Journal of Advance Research and Innovative Ideas In Education 8, no. 2 (2022): 520-523.

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