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A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
ABSTRACT The Coronavirus (COVID-19) outbreak in December 2019 has drastically
affected humans worldwide, creating a health crisis that has infected millions of lives and …
affected humans worldwide, creating a health crisis that has infected millions of lives and …
Cov-Net: A computer-aided diagnosis method for recognizing COVID-19 from chest X-ray images via machine vision
In the context of global pandemic Coronavirus disease 2019 (COVID-19) that threatens life
of all human beings, it is of vital importance to achieve early detection of COVID-19 among …
of all human beings, it is of vital importance to achieve early detection of COVID-19 among …
Medical imaging and computational image analysis in COVID-19 diagnosis: A review
Abstract Coronavirus disease (COVID-19) is an infectious disease caused by a newly
discovered coronavirus. The disease presents with symptoms such as shortness of breath …
discovered coronavirus. The disease presents with symptoms such as shortness of breath …
[HTML][HTML] Segmentation-based classification deep learning model embedded with explainable AI for COVID-19 detection in chest X-ray scans
Background and Motivation: COVID-19 has resulted in a massive loss of life during the last
two years. The current imaging-based diagnostic methods for COVID-19 detection in …
two years. The current imaging-based diagnostic methods for COVID-19 detection in …
Integrating domain knowledge into deep networks for lung ultrasound with applications to COVID-19
O Frank, N Schipper, M Vaturi, G Soldati… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Lung ultrasound (LUS) is a cheap, safe and non-invasive imaging modality that can be
performed at patient bed-side. However, to date LUS is not widely adopted due to lack of …
performed at patient bed-side. However, to date LUS is not widely adopted due to lack of …
Osegnet: Operational segmentation network for covid-19 detection using chest x-ray images
Coronavirus disease 2019 (COVID-19) has been diagnosed automatically using Machine
Learning algorithms over chest X-ray (CXR) images. However, most of the earlier studies …
Learning algorithms over chest X-ray (CXR) images. However, most of the earlier studies …
Detection of COVID-19 findings by the local interpretable model-agnostic explanations method of types-based activations extracted from CNNs
Covid-19 is a disease that affects the upper and lower respiratory tract and has fatal
consequences in individuals. Early diagnosis of COVID-19 disease is important. Datasets …
consequences in individuals. Early diagnosis of COVID-19 disease is important. Datasets …
An efficient lung disease classification from X-ray images using hybrid Mask-RCNN and BiDLSTM
Lung diseases mainly affect the inner lining of the lungs causing complications in breathing,
airway obstruction, and exhalation. Identifying lung diseases such as COVID-19 …
airway obstruction, and exhalation. Identifying lung diseases such as COVID-19 …
Progressive attention integration-based multi-scale efficient network for medical imaging analysis with application to COVID-19 diagnosis
In this paper, a novel deep learning-based medical imaging analysis framework is
developed, which aims to deal with the insufficient feature learning caused by the imperfect …
developed, which aims to deal with the insufficient feature learning caused by the imperfect …
Using a deep learning model to explore the impact of clinical data on COVID-19 diagnosis using chest X-ray
The coronavirus pandemic (COVID-19) is disrupting the entire world; its rapid global spread
threatens to affect millions of people. Accurate and timely diagnosis of COVID-19 is essential …
threatens to affect millions of people. Accurate and timely diagnosis of COVID-19 is essential …