ArticleOptik2021
COVIDetection-Net: A tailored COVID-19 detection from chest radiography images using deep learning.
Article in Optik, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Techniques, Applications, and Potential Future Opportunities in Pressure Injuries (Bedsores) Management: A Systematic Review.International journal of environmental research and public health · 2023Pooled it
- Spatial Attention-guided Hybrid Deep Learning with Sharpened Cosine Similarity for Accurate Chest X-ray InterpretationCurrent medical imaging · 2026Article
- Image complexity-based fMRI-BOLD visual network categorization across visual datasets using topological descriptors and deep-hybrid learning.Scientific reports · 2025Article
- A survey of machine learning-based methods for COVID-19 medical image analysis.Medical & biological engineering & computing · 2023Review
- Efficient breast cancer mammograms diagnosis using three deep neural networks and term variance.Scientific reports · 2023Article
- Research on lung nodule recognition algorithm based on deep feature fusion and MKL-SVM-IPSO.Scientific reports · 2022Article
- Application of Deep Learning Techniques in Diagnosis of Covid-19 (Coronavirus): A Systematic Review.Neural processing letters · 2022Review
- A fast lightweight network for the discrimination of COVID-19 and pulmonary diseases.Biomedical signal processing and control · 2022Article
- COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.Medical & biological engineering & computing · 2022Article
- Deep multi-view feature learning for detecting COVID-19 based on chest X-ray images.Biomedical signal processing and control · 2022Article
- A Data Augmentation Method for Prohibited Item X-Ray Pseudocolor Images in X-Ray Security Inspection Based on Wasserstein Generative Adversarial Network and Spatial-and-Channel Attention Block.Computational intelligence and neuroscience · 2022Article
- Human Body Performance with COVID-19 Affectation According to Virus Specification Based on Biosensor Techniques.Sensors (Basel, Switzerland) · 2021Review
- A Hybrid Convolutional Neural Network Model for Diagnosis of COVID-19 Using Chest X-ray Images.International journal of environmental research and public health · 2021Article
- Fine-Tuning Convolutional Neural Networks for COVID-19 Detection from Chest X-ray Images.Diagnostics (Basel, Switzerland) · 2021Article
- An optimized KELM approach for the diagnosis ofOptik · 2021Article
- Detection of COVID-19 in Chest X-ray Images: A Big Data Enabled Deep Learning Approach.International journal of environmental research and public health · 2021Article
- Article
- SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19.Biocybernetics and biomedical engineeringArticle
- Automated detection of COVID-19 from CT scan using convolutional neural network.Biocybernetics and biomedical engineeringArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, a medical system based on Deep Learning (DL) which we called "COVIDetection-Net" is proposed for automatic detection of new corona virus disease 2019 (COVID-19) infection from chest radiography images (CRIs). The proposed system is based on ShuffleNet and SqueezeNet architecture to extract deep learned features and Multiclass Support Vector Machines (MSVM) for detection and classification. Our dataset contains 1200 CRIs that collected from two different publicly available databases. Extensive experiments were carried out using the proposed model. The highest detection accuracy of 100 % for COVID/NonCOVID, 99.72 % for COVID/Normal/pneumonia and 94.44 % for COVID/Normal/Bacterial pneumonia/Viral pneumonia have been obtained. The proposed system superior all published methods in recall, specificity, precision, F1-Score and accuracy. Confusion Matrix (CM) and Receiver Operation Characteristics (ROC) analysis are also used to depict the performance of the proposed model. Hence the proposed COVIDetection-Net can serve as an efficient system in the current state of COVID-19 pandemic and can be used in everywhere that are facing shortage of test kits.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.