Abstract

The coronavirus disease 2019 (COVID-19) is fatal and spreading rapidly. Early detection and diagnosis of the COVID-19 infection will prevent rapid spread. This study aims to automatically detect COVID-19 through a chest computed tomography (CT) dataset. The standard models for automatic COVID-19 detection using raw chest CT images are presented. This study uses convolutional neural network (CNN), Zeiler and Fergus network (ZFNet), and dense convolutional network-121 (DenseNet121) architectures of deep convolutional neural network models. The proposed models are presented to provide accurate diagnosis for binary classification. The datasets were obtained from a public database. This retrospective study included 757 chest CT images (360 confirmed COVID-19 and 397 non-COVID-19 chest CT images). The algorithms were coded using the Python programming language. The performance metrics used were accuracy, precision, recall, F1-score, and ROC-AUC. Comparative analyses are presented between the three models by considering hyper-parameter factors to find the best model. We obtained the best performance, with an accuracy of 94,7%, a recall of 90%, a precision of 100%, and an F1-score of 94,7% from the CNN model. As a result, the CNN algorithm is more accurate and precise than the ZFNet and DenseNet121 models. This study can present a second point of view to medical staff.

Highlights

  • Machine-learning (ML) techniques have been used in medical imaging and infectious disease diagnosis (Lundervold and Lundervold, 2019; Chen et al, 2016; Ardabili et al, 2020)

  • We have proposed three models for an automatic prediction of COVID-19 using Deep learning (DL)-based using chest computed tomography (CT) images

  • We focused on the detection and prediction of COVID-19 using chest CT imaging

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Summary

Introduction

Machine-learning (ML) techniques have been used in medical imaging and infectious disease diagnosis (Lundervold and Lundervold, 2019; Chen et al, 2016; Ardabili et al, 2020). Various medical approaches are available to diagnose and detect COVID-19 in patients, such as the transcription-polymerase chain reaction (RT-PCR) test kits (Ai et al, 2020) and chest computed tomography (CT) images. Diagnosis, isolation, and treatment are critical to preventing further spread of the disease (Guner et al, 2020). Real-time polymerase chain reactions can give incorrect or inadequate information (Ai et al, 2020).

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