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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | IMPLEMENTATION TOWARDS SEVERITY PREDICTION OF COVID 19 USING MACHINE LEARNING |
| Authors Name: | Sachin Dada Shinde , Prof. Umesh Pawar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_182758
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| Published Paper Id: | IJRTI2206230 |
| Published In: | Volume 7 Issue 6, June-2022 |
| DOI: | |
| Abstract: | Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models need to be improved. Integration of artificial intelligence (AI) techniques in wireless infrastructure, real-time collection, and processing of end-user devices is now in high demand. It is now superlative to use AI to detect and predict pandemics of a colossal nature. The Coronavirus disease 2019 (COVID-19) pandemic, which originated in Wuhan China, has had disastrous effects on the global community and has overburdened advanced healthcare systems throughout the world. Globally; over 4,063,525 confirmed cases and 282,244 deaths have been recorded as of 11th May 2020, according to the European Centre for Disease Prevention and Control agency. However, the current rapid and exponential rise in the number of patients has necessitated efficient and quick prediction of the possible outcome of an infected patient for appropriate treatment using AI techniques. This paper proposes a fine-tuned SVM model boosted by algorithm. The model uses the COVID-19 patient's age, various symptoms such as dry cough, fever, etc. and it will compare with the existing dataset to predict the severity of Covid-19. |
| Keywords: | Covid-19, severity, prediction, python, svm etc. |
| Cite Article: | "IMPLEMENTATION TOWARDS SEVERITY PREDICTION OF COVID 19 USING MACHINE LEARNING", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.1559 - 1565, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206230.pdf |
| Downloads: | 000205229 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2206230
Registration ID:182758
Published In: Volume 7 Issue 6, June-2022
DOI (Digital Object Identifier):
Page No: 1559 - 1565 Country: Ahmednagar, Maharashtra, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2206230 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2206230 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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