文章基本信息

标题：A Case Study on Design of Covid-19 Detection and Alerting System Using Machine Learning Techniques
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作者：A. Parkavi ; V. Sangeetha ; Sini Anna Alex 等
期刊名称：Webology
印刷版ISSN：1735-188X
出版年度：2022
卷号：19
期号：1
页码：1358-1386
DOI：10.14704/WEB/V19I1/WEB19091
语种：English
出版社：University of Tehran
摘要：Coronavirus or 2019-nCoV is not, at this point, pandemic but instead endemic, with in excess of 14 million complete cases all throughout the planet getting the infection. At present, there is no particular treatment or solution for Coronavirus, and hence living with the sickness and its manifestations is unavoidable. The connection coefficient examination between different needy and free highlights was done to decide a strength connection between every reliant element and autonomous component of the dataset before building up the models. The database is divided into two parts, 80% of the database is used for model training and the remaining 20% is used for model testing and evaluation. In 2019, early Coronavirus predictions is useful to reduce colossal weight on medical service panels through the diagnosis of coronavirus patients. In the proposed work in this paper, Naive Bayes, Decision tree, Support Vector Machine (SVM) and Artificial neural network (ANN) models are used for forecasting COVID-19 prediction and occurrences.
关键词：Covid 19 Detection;Prediction;Correlation Analysis;Android App for Covid 19