Comparative Intrepretation Of Machine Learning Algorithms In Predicting The Cardiovascular Death Rate For Covid-19 Data

Krithika, D. R. and Rohini, K. (2021) Comparative Intrepretation Of Machine Learning Algorithms In Predicting The Cardiovascular Death Rate For Covid-19 Data. 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). pp. 394-400.

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Abstract

Every year 31% of people die from cardiovascular disease
worldwide. The big data analytics technique is very useful
to Identify Heart disease and COVID-19. To control the
COVID-19 spread around the world and many of the companies adapting this technology and also remote places patient reports doctors view easily to analyze health condition of the patient using IOT based big data. In 2019 COVID-19 (Novel coronavirus Disease) was recognized. COVID-19 signs of CT scan include pleural thickening and vascular enlargement. Nucleic acid detection and epidemiological tracing are using Chest CT scans counteract. To understanding of the disease COVIDE-19 the Researchers are using ML, AI (Artificial Intelligence) and natural language processing. We are using big data analytics to track the spread of this coronavirus. In this paper we discuss about Comparison of Tools in Big data Analytics using machine learning Algorithm.

Item Type: Article
Subjects: Computer Science Engineering > Machine Learning
Divisions: Computer Science
Depositing User: Mr IR Admin
Date Deposited: 16 Sep 2024 05:53
Last Modified: 16 Sep 2024 05:53
URI: https://ir.vistas.ac.in/id/eprint/6170

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