A systematic review on deep structured learning for COVID-19 screening using chest CT from 2020 to 2022
KC Santosh, D GhoshRoy, S Nakarmi - Healthcare, 2023 - mdpi.com
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 …
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 …
COVID-19 detection: A systematic review of machine and deep learning-based approaches utilizing chest X-rays and CT scans
KR Bhatele, A Jha, D Tiwari, M Bhatele, S Sharma… - Cognitive …, 2024 - Springer
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 …
Detection of COVID-19 based on chest X-rays using deep learning
The coronavirus disease (COVID-19) is rapidly spreading around the world. Early diagnosis
and isolation of COVID-19 patients has proven crucial in slowing the disease's spread. One …
and isolation of COVID-19 patients has proven crucial in slowing the disease's spread. One …
Pneumonia detection proposing a hybrid deep convolutional neural network based on two parallel visual geometry group architectures and machine learning …
Pneumonia is an acute respiratory infection that has led to significant deaths of people
worldwide. This lung disease is more common in people older than 65 and children under …
worldwide. This lung disease is more common in people older than 65 and children under …
[Retracted] A Rapid Artificial Intelligence‐Based Computer‐Aided Diagnosis System for COVID‐19 Classification from CT Images
The excessive number of COVID‐19 cases reported worldwide so far, supplemented by a
high rate of false alarms in its diagnosis using the conventional polymerase chain reaction …
high rate of false alarms in its diagnosis using the conventional polymerase chain reaction …
Automatic COVID-19 detection using exemplar hybrid deep features with X-ray images
COVID-19 and pneumonia detection using medical images is a topic of immense interest in
medical and healthcare research. Various advanced medical imaging and machine learning …
medical and healthcare research. Various advanced medical imaging and machine learning …
Vision transformer outperforms deep convolutional neural network-based model in classifying X-ray images
The standard approach for automated clinical image diagnosis is being held with the use of
Convolutional Neural Networks (CNN) for a decade. Vision Transformers (ViT) are new in …
Convolutional Neural Networks (CNN) for a decade. Vision Transformers (ViT) are new in …
[PDF][PDF] COVID-19 Detection on x-ray images using a combining mechanism of pre-trained CNNs
The COVID-19 infection was sparked by the severe acute respiratory syndrome SARS-CoV-
2, as mentioned by the World Health Organization, and originated in Wuhan, Republic of …
2, as mentioned by the World Health Organization, and originated in Wuhan, Republic of …
[HTML][HTML] Swin-textural: A novel textural features-based image classification model for COVID-19 detection on chest computed tomography
Background Chest computed tomography (CT) has a high sensitivity for detecting COVID-19
lung involvement and is widely used for diagnosis and disease monitoring. We proposed a …
lung involvement and is widely used for diagnosis and disease monitoring. We proposed a …