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[HTML][HTML] A systematic review on deep structured learning for COVID-19 screening using chest CT from 2020 to 2022
The emergence of the COVID-19 pandemic in Wuhan in 2019 led to the discovery of a novel
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
Deep learning for COVID-19 screening using chest x-rays in 2020: A systematic review
Artificial Intelligence (AI) has promoted countless contributions in the field of healthcare and
medical imaging. In this paper, we thoroughly analyze peer-reviewed research …
medical imaging. In this paper, we thoroughly analyze peer-reviewed research …
[PDF][PDF] Efficient Deep-Learning-Based Autoencoder Denoising Approach for Medical Image Diagnosis.
Effective medical diagnosis is dramatically expensive, especially in third-world countries.
One of the common diseases is pneumonia, and because of the remarkable similarity …
One of the common diseases is pneumonia, and because of the remarkable similarity …
A novel Covid-19 and pneumonia classification method based on F-transform
Nowadays, Covid-19 is the most important disease that affects daily life globally. Therefore,
many methods are offered to fight against Covid-19. In this paper, a novel fuzzy tree …
many methods are offered to fight against Covid-19. In this paper, a novel fuzzy tree …
Automatic diagnosis of COVID-19 from CT images using CycleGAN and transfer learning
The outbreak of the corona virus disease (COVID-19) has changed the lives of most people
on Earth. Given the high prevalence of this disease, its correct diagnosis in order to …
on Earth. Given the high prevalence of this disease, its correct diagnosis in order to …
Variational autoencoder based imbalanced COVID-19 detection using chest X-ray images
Early and fast detection of disease is essential for the fight against COVID-19 pandemic.
Researchers have focused on develo** robust and cost-effective detection methods using …
Researchers have focused on develo** robust and cost-effective detection methods using …
Classification of COVID‐19 and Pneumonia Using Deep Transfer Learning
The World Health Organization (WHO) recognized COVID‐19 as the cause of a global
pandemic in 2019. COVID‐19 is caused by SARS‐CoV‐2, which was identified in China in …
pandemic in 2019. COVID‐19 is caused by SARS‐CoV‐2, which was identified in China in …
[HTML][HTML] Discriminative learning approach based on flexible mixture model for medical data categorization and recognition
In this paper, we propose a novel hybrid discriminative learning approach based on shifted-
scaled Dirichlet mixture model (SSDMM) and Support Vector Machines (SVMs) to address …
scaled Dirichlet mixture model (SSDMM) and Support Vector Machines (SVMs) to address …
[HTML][HTML] A dual-stage vocabulary of features (VoF)-based technique for COVID-19 variants' classification
Novel coronavirus, known as COVID-19, is a very dangerous virus. Initially detected in
China, it has since spread all over the world causing many deaths. There are several …
China, it has since spread all over the world causing many deaths. There are several …
Bayesian learning of shifted-scaled dirichlet mixture models and its application to early COVID-19 detection in chest X-ray images
Early diagnosis and assessment of fatal diseases and acute infections on chest X-ray (CXR)
imaging may have important therapeutic implications and reduce mortality. In fact, many …
imaging may have important therapeutic implications and reduce mortality. In fact, many …