Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Colorectal polyp region extraction using saliency detection network with neutrosophic enhancement
Colorectal polyp recognition is crucial for early colorectal cancer detection and treatment.
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
Covid-19 detection: A systematic review of machine and deep learning-based approaches utilizing chest x-rays and ct scans
This review study presents the state-of-the-art machine and deep learning-based COVID-19
detection approaches utilizing the chest X-rays or computed tomography (CT) scans. This …
detection approaches utilizing the chest X-rays or computed tomography (CT) scans. This …
A deep transfer learning-based convolution neural network model for COVID-19 detection using computed tomography scan images for medical applications
ND Kathamuthu, S Subramaniam, QH Le… - … in Engineering Software, 2023 - Elsevier
Abstract The Coronavirus (COVID-19) has become a critical and extreme epidemic because
of its international dissemination. COVID-19 is the world's most serious health, economic …
of its international dissemination. COVID-19 is the world's most serious health, economic …
A survey on deep transfer learning to edge computing for mitigating the COVID-19 pandemic
Global Health sometimes faces pandemics as are currently facing COVID-19 disease. The
spreading and infection factors of this disease are very high. A huge number of people from …
spreading and infection factors of this disease are very high. A huge number of people from …
COVID-19 cough sound symptoms classification from scalogram image representation using deep learning models
Deep Learning shows promising performance in diverse fields and has become an
emerging technology in Artificial Intelligence. Recent visual recognition is based on the …
emerging technology in Artificial Intelligence. Recent visual recognition is based on the …
BCS-Net: Boundary, context, and semantic for automatic COVID-19 lung infection segmentation from CT images
The spread of COVID-19 has brought a huge disaster to the world, and the automatic
segmentation of infection regions can help doctors to make diagnosis quickly and reduce …
segmentation of infection regions can help doctors to make diagnosis quickly and reduce …
A pneumonia diagnosis scheme based on hybrid features extracted from chest radiographs using an ensemble learning algorithm
Pneumonia is a fatal disease responsible for almost one in five child deaths worldwide.
Many develo** countries have high mortality rates due to pneumonia because of the …
Many develo** countries have high mortality rates due to pneumonia because of the …
A comprehensive review of deep learning-based methods for COVID-19 detection using chest X-ray images
The novel coronavirus disease 2019 (COVID-19) added tremendous pressure on healthcare
services worldwide. COVID-19 early detection is of the utmost importance to control the …
services worldwide. COVID-19 early detection is of the utmost importance to control the …
CovidCoughNet: A new method based on convolutional neural networks and deep feature extraction using pitch-shifting data augmentation for covid-19 detection …
G Celik - Computers in Biology and Medicine, 2023 - Elsevier
This study proposes a new deep learning-based method that demonstrates high
performance in detecting Covid-19 disease from cough, breath, and voice signals. This …
performance in detecting Covid-19 disease from cough, breath, and voice signals. This …