ArticleAnnals of operations research2022
A novel deep neural network model based Xception and genetic algorithm for detection of COVID-19 from X-ray images.
Article in Annals of operations research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- A two-stage preprocessing and classification approach for accurate COVID-19 detection in X-ray images.Scientific reports · 2026Article
- Hybrid model integration with explainable AI for brain tumor diagnosis: a unified approach to MRI analysis and prediction.Scientific reports · 2025Article
- A Convolutional Mixer-Based Deep Learning Network for Alzheimer's Disease Classification from Structural Magnetic Resonance Imaging.Diagnostics (Basel, Switzerland) · 2025Article
- Comparison of deep learning models in automatic classification of coffee bean species.PeerJ. Computer science · 2025Article
- Advancements in rice disease detection through convolutional neural networks: A comprehensive review.Heliyon · 2024Review
- MedKnee: A New Deep Learning-Based Software for Automated Prediction of Radiographic Knee Osteoarthritis.Diagnostics (Basel, Switzerland) · 2024Article
- Cloud-Based Quad Deep Ensemble Framework for the Detection of COVID-19 Omicron and Delta Variants.Diagnostics (Basel, Switzerland) · 2023Article
- What Is Machine Learning, Artificial Neural Networks and Deep Learning?-Examples of Practical Applications in Medicine.Diagnostics (Basel, Switzerland) · 2023Review
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Abstract
The coronavirus first appeared in China in 2019, and the World Health Organization (WHO) named it COVID-19. Then WHO announced this illness as a worldwide pandemic in March 2020. The number of cases, infections, and fatalities varied considerably worldwide. Because the main characteristic of COVID-19 is its rapid spread, doctors and specialists generally use PCR tests to detect the COVID-19 virus. As an alternative to PCR, X-ray images can help diagnose illness using artificial intelligence (AI). In medicine, AI is commonly employed. Convolutional neural networks (CNN) and deep learning models make it simple to extract information from images. Several options exist when creating a deep CNN. The possibilities include network depth, layer count, layer type, and parameters. In this paper, a novel Xception-based neural network is discovered using the genetic algorithm (GA). GA finds better alternative networks and parameters during iterations. The best network discovered with GA is tested on a COVID-19 X-ray image dataset. The results are compared with other networks and the results of papers in the literature. The novel network of this paper gives more successful results. The accuracy results are 0.996, 0.989, and 0.924 for two-class, three-class, and four-class datasets, respectively.
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