Unknown

Dataset Information

0

Computer-aided detection of COVID-19 from X-ray images using multi-CNN and Bayesnet classifier.


ABSTRACT: Corona virus disease-2019 (COVID-19) is a pandemic caused by novel coronavirus. COVID-19 is spreading rapidly throughout the world. The gold standard for diagnosing COVID-19 is reverse transcription-polymerase chain reaction (RT-PCR) test. However, the facility for RT-PCR test is limited, which causes early diagnosis of the disease difficult. Easily available modalities like X-ray can be used to detect specific symptoms associated with COVID-19. Pre-trained convolutional neural networks are widely used for computer-aided detection of diseases from smaller datasets. This paper investigates the effectiveness of multi-CNN, a combination of several pre-trained CNNs, for the automated detection of COVID-19 from X-ray images. The method uses a combination of features extracted from multi-CNN with correlation based feature selection (CFS) technique and Bayesnet classifier for the prediction of COVID-19. The method was tested using two public datasets and achieved promising results on both the datasets. In the first dataset consisting of 453 COVID-19 images and 497 non-COVID images, the method achieved an AUC of 0.963 and an accuracy of 91.16%. In the second dataset consisting of 71 COVID-19 images and 7 non-COVID images, the method achieved an AUC of 0.911 and an accuracy of 97.44%. The experiments performed in this study proved the effectiveness of pre-trained multi-CNN over single CNN in the detection of COVID-19.

SUBMITTER: Abraham B 

PROVIDER: S-EPMC7467028 | biostudies-literature | 2020 Oct-Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Computer-aided detection of COVID-19 from X-ray images using multi-CNN and Bayesnet classifier.

Abraham Bejoy B   Nair Madhu S MS  

Biocybernetics and biomedical engineering 20200902 4


Corona virus disease-2019 (COVID-19) is a pandemic caused by novel coronavirus. COVID-19 is spreading rapidly throughout the world. The gold standard for diagnosing COVID-19 is reverse transcription-polymerase chain reaction (RT-PCR) test. However, the facility for RT-PCR test is limited, which causes early diagnosis of the disease difficult. Easily available modalities like X-ray can be used to detect specific symptoms associated with COVID-19. Pre-trained convolutional neural networks are wide  ...[more]

Similar Datasets

| S-EPMC9122742 | biostudies-literature
| S-EPMC9568999 | biostudies-literature
| S-EPMC8044917 | biostudies-literature
| S-EPMC9575860 | biostudies-literature
| S-EPMC7510591 | biostudies-literature
| S-EPMC7752539 | biostudies-literature
| S-EPMC9975856 | biostudies-literature
| S-EPMC8110795 | biostudies-literature
| S-EPMC7273278 | biostudies-literature
| S-EPMC9333103 | biostudies-literature