About: Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods

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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	Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods
Creator	Barstugan, Mucahid Ozkaya, Umut Ozturk, Saban
Source	ArXiv
abstract	This study presents early phase detection of Coronavirus (COVID-19), which is named by World Health Organization (WHO), by machine learning methods. The detection process was implemented on abdominal Computed Tomography (CT) images. The expert radiologists detected from CT images that COVID-19 shows different behaviours from other viral pneumonia. Therefore, the clinical experts specify that COV/.ID-19 virus needs to be diagnosed in early phase. For detection of the COVID-19, four different datasets were formed by taking patches sized as 16x16, 32x32, 48x48, 64x64 from 150 CT images. The feature extraction process was applied to patches to increase the classification performance. Grey Level Co-occurrence Matrix (GLCM), Local Directional Pattern (LDP), Grey Level Run Length Matrix (GLRLM), Grey-Level Size Zone Matrix (GLSZM), and Discrete Wavelet Transform (DWT) algorithms were used as feature extraction methods. Support Vector Machines (SVM) classified the extracted features. 2-fold, 5-fold and 10-fold cross-validations were implemented during the classification process. Sensitivity, specificity, accuracy, precision, and F-score metrics were used to evaluate the classification performance. The best classification accuracy was obtained as 99.68% with 10-fold cross-validation and GLSZM feature extraction method.
has issue date	2020-03-20(xsd:dateTime)
has license	arxiv
sha1sum (hex)	26d11d2eab9b9842130e1fef2ce6f6e22324556d
resource representing a document's title	Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods
resource representing a document's body	covid:26d11d2eab9b9842130e1fef2ce6f6e22324556d#body_text
is schema:about of	named entity 'Methods' named entity 'FOLD' named entity 'evaluate' named entity 'Support Vector Machines' named entity 'Classification' named entity 'Wavelet Transform' named entity 'Sensitivity, specificity' named entity 'F-score' named entity 'Machine Learning Methods' named entity 'COVID-19' named entity 'feature extraction' named entity 'machine learning methods' named entity 'high-pass filter' named entity 'feature extraction' named entity 'cross-validation' named entity 'DWT' named entity 'algorithm' named entity 'COVID-19' named entity 'fever' named entity 'DWT' named entity 'blood test results' named entity 'feature extraction' named entity 'COVID-19 disease' named entity 'DWT' named entity 'CT image' named entity 'DWT' named entity 'hyperplane' named entity 'pixel' named entity 'human body' named entity 'Grey Level' named entity 'DWT' named entity 'Feature extraction' named entity 'cross-validation' named entity 'Wuhan' named entity 'COVID-19' named entity 'COVID-19' named entity 'COVID-19 disease' named entity 'CT images' named entity 'LDP' named entity 'COVID-19 disease' named entity 'LDP' named entity 'SVM' named entity 'SVM' named entity 'coefficient matrix' named entity 'DWT' named entity 'LDP' named entity 'DWT' named entity 'CT image' named entity 'CT image' named entity 'CT images' named entity 'lung' named entity 'secondary infection' named entity 'extracted features' named entity 'SVM' named entity 'Grey Level' named entity 'SVM' named entity 'Size Zone Matrix' named entity 'intensive care unit' named entity 'input size' named entity 'feature extraction' named entity 'cross validation' named entity 'feature extraction' named entity 'SVM' named entity 'algorithm' named entity 'feature extraction' named entity 'feature vector' named entity 'feature extraction' named entity 'binary classifier' named entity 'feature vector' named entity 'SVM' named entity 'Dice similarity coefficient' named entity 'feature vector' named entity 'nonlinear method' named entity 'feature extraction' named entity 'COVID-19' named entity 'SVM' named entity 'Grey Level' named entity 'COVID-19' named entity 'feature extraction' named entity 'COVID-19' named entity 'greylevel' named entity 'CT image' named entity 'Directional Patterns' named entity 'COVID-19' named entity 'SVM'

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