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About:
Distinguishing L and H phenotypes of COVID-19 using a single x-ray image
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covidontheweb.inria.fr
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
title
Distinguishing L and H phenotypes of COVID-19 using a single x-ray image
Creator
Islam, Mohammad
Fleischer, Jason
source
MedRxiv
abstract
Recent observations have shown that there are two types of COVID-19 response: an H phenotype with high lung elastance and weight, and an L phenotype with low measures. H-type patients have pneumonia-like thickening of the lungs and require ventilation to survive; L-type patients have clearer lungs that may be injured by mechanical assistance. As treatment protocols differ between the two types, and the number of ventilators is limited, it is vital to classify patients appropriately. To date, the only way to confirm phenotypes is through high-resolution computed tomography. Here, we identify L- and H-type patients from their frontal chest x-rays using feature-embedded machine learning. We then apply the categorization to multiple images from the same patient, extending it to detect and monitor disease progression and recovery. The results give an immediate criterion for coronavirus triage and provide a methodology for respiratory diseases beyond COVID-19.
has issue date
2020-05-03
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bibo:doi
10.1101/2020.04.27.20081984
has license
medrxiv
sha1sum (hex)
0ed35755ab7f427bc62d83859af5a3415e9378b5
schema:url
https://doi.org/10.1101/2020.04.27.20081984
resource representing a document's title
Distinguishing L and H phenotypes of COVID-19 using a single x-ray image
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covid:0ed35755ab7f427bc62d83859af5a3415e9378b5#body_text
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schema:about
of
named entity 'H-type'
named entity 'mechanical'
named entity 'phenotype'
named entity 'X-RAY IMAGE'
named entity 'WEIGHT'
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