A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron

A Khan, SH Khan, M Saif, A Batool… - … of Experimental & …, 2024 - Taylor & Francis
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 …

Cov-Net: A computer-aided diagnosis method for recognizing COVID-19 from chest X-ray images via machine vision

H Li, N Zeng, P Wu, K Clawson - Expert Systems with Applications, 2022 - Elsevier
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 …

Medical imaging and computational image analysis in COVID-19 diagnosis: A review

S Nabavi, A Ejmalian, ME Moghaddam, AA Abin… - Computers in Biology …, 2021 - Elsevier
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 …

[HTML][HTML] Segmentation-based classification deep learning model embedded with explainable AI for COVID-19 detection in chest X-ray scans

N Sharma, L Saba, NN Khanna, MK Kalra, MM Fouda… - Diagnostics, 2022 - mdpi.com
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 …

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 …

Osegnet: Operational segmentation network for covid-19 detection using chest x-ray images

A Degerli, S Kiranyaz, MEH Chowdhury… - … Conference on Image …, 2022 - ieeexplore.ieee.org
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 …

Detection of COVID-19 findings by the local interpretable model-agnostic explanations method of types-based activations extracted from CNNs

M Toğaçar, N Muzoğlu, B Ergen, BSB Yarman… - … Signal Processing and …, 2022 - Elsevier
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 …

An efficient lung disease classification from X-ray images using hybrid Mask-RCNN and BiDLSTM

V Indumathi, R Siva - Biomedical Signal Processing and Control, 2023 - Elsevier
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 …

Progressive attention integration-based multi-scale efficient network for medical imaging analysis with application to COVID-19 diagnosis

T **e, Z Wang, H Li, P Wu, H Huang, H Zhang… - Computers in Biology …, 2023 - Elsevier
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 …

Using a deep learning model to explore the impact of clinical data on COVID-19 diagnosis using chest X-ray

IU Khan, N Aslam, T Anwar, HS Alsaif, SMB Chrouf… - Sensors, 2022 - mdpi.com
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 …