About: A HYBRID KNOWLEDGE-BASED AND MODIFIED REGRESSION ANALYSIS APPROACH FOR COVID-19 TRACKING IN USA

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About: A HYBRID KNOWLEDGE-BASED AND MODIFIED REGRESSION ANALYSIS APPROACH FOR COVID-19 TRACKING IN USA Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	A HYBRID KNOWLEDGE-BASED AND MODIFIED REGRESSION ANALYSIS APPROACH FOR COVID-19 TRACKING IN USA
Creator	Hussein, Rafaat
source	MedRxiv
abstract	Since its appearance in 2019, the covid-19 virus deluged the world with unprecedented data in short time. Despite the countless worldwide pertinent studies and advanced technologies, the spread is neither contained nor defeated. In fact, there is a record surge in the number of confirmed new cases since July 2020. This article presents a new predictive Knowledge-based (KB) toolkit named CORVITT (Corona Virus Tracking Toolkit) and modified linear regression model. This hybrid approach uses the confirmed new cases and demographic data, implemented. CORVITT is not an epidemiological model, in the sense that it does not model disease transmission, nor does it use underlying epidemiological parameters like the reproductive rate. It forecasts the spread in order to assist the official to make proactive intervention.
has issue date	2020-07-29(xsd:dateTime)
bibo:doi	10.1101/2020.07.26.20162347
has license	medrxiv
sha1sum (hex)	729995f981164dace9e66e2c77f18ee2a1aef41c
schema:url	https://doi.org/10.1101/2020.07.26.20162347
resource representing a document's title	A HYBRID KNOWLEDGE-BASED AND MODIFIED REGRESSION ANALYSIS APPROACH FOR COVID-19 TRACKING IN USA
resource representing a document's body	covid:729995f981164dace9e66e2c77f18ee2a1aef41c#body_text
is schema:about of	named entity 'epidemiological' named entity 'Since' named entity 'Despite' named entity 'ASSIST' named entity 'APPEARANCE' »more»

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