COVID-19 image classification using deep learning: Advances, challenges and opportunities
Abstract Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
A systematic review on federated learning in medical image analysis
MF Sohan, A Basalamah - IEEE Access, 2023 - ieeexplore.ieee.org
Federated Learning (FL) obtained a lot of attention to the academic and industrial
stakeholders from the beginning of its invention. The eye-catching feature of FL is handling …
stakeholders from the beginning of its invention. The eye-catching feature of FL is handling …
A hybrid deep learning-based approach for brain tumor classification
Brain tumors (BTs) are spreading very rapidly across the world. Every year, thousands of
people die due to deadly brain tumors. Therefore, accurate detection and classification are …
people die due to deadly brain tumors. Therefore, accurate detection and classification are …
[HTML][HTML] A deep learning architecture for multi-class lung diseases classification using chest X-ray (CXR) images
In 2019, the world experienced the rapid outbreak of the Covid-19 pandemic creating an
alarming situation worldwide. The virus targets the respiratory system causing pneumonia …
alarming situation worldwide. The virus targets the respiratory system causing pneumonia …
[Retracted] COVID‐19 Detection Based on Lung Ct Scan Using Deep Learning Techniques
SV Kogilavani, J Prabhu, R Sandhiya… - … Methods in Medicine, 2022 - Wiley Online Library
SARS‐CoV‐2 is a novel virus, responsible for causing the COVID‐19 pandemic that has
emerged as a pandemic in recent years. Humans are becoming infected with the virus. In …
emerged as a pandemic in recent years. Humans are becoming infected with the virus. In …
A lightweight CNN-based network on COVID-19 detection using X-ray and CT images
ML Huang, YC Liao - Computers in Biology and Medicine, 2022 - Elsevier
Background and objectives The traditional method of detecting COVID-19 disease mainly
rely on the interpretation of computer tomography (CT) or X-ray images (X-ray) by doctors or …
rely on the interpretation of computer tomography (CT) or X-ray images (X-ray) by doctors or …
D2BOF-COVIDNet: A Framework of Deep Bayesian Optimization and Fusion-Assisted Optimal Deep Features for COVID-19 Classification Using Chest X-ray and MRI …
Background and Objective: In 2019, a corona virus disease (COVID-19) was detected in
China that affected millions of people around the world. On 11 March 2020, the WHO …
China that affected millions of people around the world. On 11 March 2020, the WHO …
Btc-fcnn: fast convolution neural network for multi-class brain tumor classification
Timely prognosis of brain tumors has a crucial role for powerful healthcare of remedy-
making plans. Manual classification of the brain tumors in magnetic resonance imaging …
making plans. Manual classification of the brain tumors in magnetic resonance imaging …
Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images
Chest X-ray images are used in deep convolutional neural networks for the detection of
COVID-19, the greatest human challenge of the 21st century. Robustness to noise and …
COVID-19, the greatest human challenge of the 21st century. Robustness to noise and …
Concatenation of pre-trained convolutional neural networks for enhanced COVID-19 screening using transfer learning technique
Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory
symptoms such as fever, cough, dyspnea, pneumonia, and weariness being typical in the …
symptoms such as fever, cough, dyspnea, pneumonia, and weariness being typical in the …