About: Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)
Creator	Montoya, Carlos Bitar, Patricia Dinamarca, Victor Fuentes, Jorge Galvez, Marcelo Rojas, Gonzalo Schlotterbeck, Nicolas
Source	MedRxiv
abstract	COVID-19 is a pandemic infectious disease caused by the SARS-CoV-2 virus, having reached more than 210 countries and territories. It produces symptoms such as fever, dry cough, dyspnea, fatigue, pneumonia, and radiological manifestations. The most common reported RX and CT findings include lung consolidation and ground-glass opacities. In this paper, we describe a machine learning-based system (XrayCoviDetector; www.covidetector.net), that detects automatically, the probability that a thorax radiological image includes COVID-19 lung patterns. XrayCoviDetector has an accuracy of 0.93, a sensitivity of 0.96, and a specificity of 0.90.
has issue date	2020-08-23(xsd:dateTime)
bibo:doi	10.1101/2020.08.20.20178723
has license	medrxiv
sha1sum (hex)	7a0f7d94cf2f18491b4cf51a623c2d3b19cd7418
schema:url	https://doi.org/10.1101/2020.08.20.20178723
resource representing a document's title	Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)
resource representing a document's body	covid:7a0f7d94cf2f18491b4cf51a623c2d3b19cd7418#body_text
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