Impartially Validated Multiple Deep-Chain Models to Detect COVID-19 in Chest X-ray Using Latent Space Radiomics

The COVID-19 pandemic continues to spread globally at a rapid pace, and its rapid detection remains a challenge due to its rapid infectivity and limited testing availability. One of the simply available imaging modalities in clinical routine involves chest X-ray (CXR), which is often used for diagno...

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Vydané v:	Journal of clinical medicine Ročník 10; číslo 14; s. 3100
Hlavní autori:	Yousefi, Bardia, Kawakita, Satoru, Amini, Arya, Akbari, Hamed, Advani, Shailesh M., Akhloufi, Moulay, Maldague, Xavier P. V., Ahadian, Samad
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 14.07.2021 MDPI
Predmet:	Accuracy Artificial intelligence Biomarkers Clinical medicine Coronaviruses COVID-19 Disease transmission Health care Machine learning Medical imaging Neural networks Pandemics Pneumonia Radiomics Viral infections imaging biomarker chest X-ray imaging deep latent space radiomics COVID-19 detection deep convolutional autoencoder (ConvAE) 2D U-Net model deep-learning features
ISSN:	2077-0383, 2077-0383
On-line prístup:	Získať plný text
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