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About:
Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)
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covidontheweb.inria.fr
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Academic Article
research paper
schema:ScholarlyArticle
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
title
Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)
Creator
Montoya, Carlos
Bitar, Patricia
Dinamarca, Victor
Fuentes, Jorge
Galvez, Marcelo
»more»
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
(
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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
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Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)
resource representing a document's body
covid:7a0f7d94cf2f18491b4cf51a623c2d3b19cd7418#body_text
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schema:about
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named entity 'dry cough'
named entity 'radiographic'
named entity 'COUNTRIES'
named entity 'IS A'
named entity 'SYMPTOMS'
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