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FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images
- Source :
- Evolving Systems
- Publication Year :
- 2021
- Publisher :
- Springer Berlin Heidelberg, 2021.
-
Abstract
- COVID-19 is an acronym for coronavirus disease 2019. Initially, it was called 2019-nCoV, and later International Committee on Taxonomy of Viruses (ICTV) termed it SARS-CoV-2. On 30th January 2020, the World Health Organization (WHO) declared it a pandemic. With an increasing number of COVID-19 cases, the available medical infrastructure is essential to detect the suspected cases. Medical imaging techniques such as Computed Tomography (CT), chest radiography can play an important role in the early screening and detection of COVID-19 cases. It is important to identify and separate the cases to stop the further spread of the virus. Artificial Intelligence can play an important role in COVID-19 detection and decreases the workload on collapsing medical infrastructure. In this paper, a deep convolutional neural network-based architecture is proposed for the COVID-19 detection using chest radiographs. The dataset used to train and test the model is available on different public repositories. Despite having the high accuracy of the model, the decision on COVID-19 should be made in consultation with the trained medical clinician.
- Subjects :
- medicine.medical_specialty
Control and Optimization
Coronavirus disease 2019 (COVID-19)
Computer science
Radiography
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Convolutional neural network
02 engineering and technology
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
0202 electrical engineering, electronic engineering, information engineering
Medical imaging
medicine
Medical physics
Original Paper
business.industry
COVID-19 classification
Deep learning
Chest X-ray
Workload
Computer Science Applications
Control and Systems Engineering
Modeling and Simulation
X ray image
020201 artificial intelligence & image processing
Artificial intelligence
business
FocusCovid
Subjects
Details
- Language :
- English
- ISSN :
- 18686486 and 18686478
- Database :
- OpenAIRE
- Journal :
- Evolving Systems
- Accession number :
- edsair.doi.dedup.....0dce8ebf3ed1fb7eb3cb781773cfb5d6