A large margin piecewise linear classifier with fusion of deep features in the diagnosis of COVID-19

The world has experienced epidemics of coronavirus infections several times over the last two decades. Recent studies have shown that using medical imaging techniques can be useful in developing an automatic computer-aided diagnosis system to detect pandemic diseases with high accuracy at an early s...

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Veröffentlicht in:	Computers in biology and medicine 2021-12, Vol.139, p.104927-104927, Article 104927
Hauptverfasser:	Azouji, Neda, Sami, Ashkan, Taheri, Mohammad, Müller, Henning
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Canonical Correlation Analysis Classification Classifiers Computer-aided diagnosis (CAD) Coronaviruses Correlation analysis COVID-19 Datasets Deep feature extraction Deep Learning Diagnosis Disease transmission Epidemics Feature extraction Humans Imaging techniques Large margin classifier Medical diagnosis Medical imaging MERS Middle East respiratory syndrome Neural networks Neural Networks, Computer Pandemics Pneumonia Pneumonia, Viral Respiratory diseases SARS SARS-CoV-2 Severe acute respiratory syndrome Support vector machines Transfer learning Viral diseases X-ray X-rays
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