Effective COVID-19 disease identification using correlation coefficient absolute feature selection and logistic boosting neural network algorithm
- 20 June 2024
- journal article
- research article
- Published by Springer Nature in SN Computer Science
- Vol. 5 (6) , 1-9
Abstract
No abstract availableKeywords
This publication has 22 references indexed in Scilit:
- Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networksPattern Analysis and Applications, 2021
- Deep learning for diagnosis of COVID-19 using 3D CT scansComputers in Biology and Medicine, 2021
- A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19)European Radiology, 2021
- Hybrid-COVID: a novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray imagesPhysical and Engineering Sciences in Medicine, 2020
- CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray imagesComputer Methods and Programs in Biomedicine, 2020
- Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networksApplied Intelligence, 2020
- COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approachesComputers in Biology and Medicine, 2020
- Automated detection of COVID-19 cases using deep neural networks with X-ray imagesComputers in Biology and Medicine, 2020
- Classification of COVID-19 patients from chest CT images using multi-objective differential evolution–based convolutional neural networksEuropean Journal of Clinical Microbiology & Infectious Diseases, 2020
- Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networksPhysical and Engineering Sciences in Medicine, 2020