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Covid-19 Health Prediction using Supervised Learning with Optimization

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Covid-19 Health Prediction using Supervised Learning with Optimization


Akash Malvi | Nikesh Gupta



Akash Malvi | Nikesh Gupta "Covid-19 Health Prediction using Supervised Learning with Optimization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-6, December 2023, pp.636-643, URL: https://www.ijtsrd.com/papers/ijtsrd61266.pdf

The assessment of infection is significant for Covid 19 as the antigen pack and RTPCR are imperfect and ought to be better for diagnosing such sickness. Continuous Return Transcription (constant talk record polymerase chain). Medical services rehearse incorporate the assortment of different kinds of patient information to assist the doctor with diagnosing the patient's wellbeing. This information could be basic side effects, first analysis by a specialist, or an inside and out research facility test. This information is in this manner utilized for examinations simply by a specialist, who thusly utilizes his specific clinical abilities to track down the illness. To group Covid 19 sickness datasets like gentle, center and serious infections, the proposed model uses the idea of controlled machine training and GWO-advancement to manage in the event that the patient is impacted or not. Effectiveness investigation is determined and thought about of infection information for the two calculations. The consequences of the reenactments outline the compelling nature and intricacy of the informational index for the reviewing strategies. Contrasted with SVM, the proposed model gives 7.8 percent further developed forecast exactness. The forecast exactness is 8% better than the SVM. This outcome F1 score of 2% is better than an SVM conjecture.

SVM, RTPCR, GWO, Accuracy, Precision, F1-Score


IJTSRD61266
Volume-7 | Issue-6, December 2023
636-643
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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