Automated detection and forecasting of covid-19 using deep learning techniques: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Neurocomputing, 2024 - Elsevier
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 …

Applications of artificial intelligence in battling against covid-19: A literature review

M Tayarani - Chaos, Solitons and Fractals, 2020 - researchprofiles.herts.ac.uk
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …

A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset

M Rahimzadeh, A Attar, SM Sakhaei - Biomedical Signal Processing and …, 2021 - Elsevier
This paper aims to propose a high-speed and accurate fully-automated method to detect
COVID-19 from the patient's chest CT scan images. We introduce a new dataset that …

Contrastive cross-site learning with redesigned net for COVID-19 CT classification

Z Wang, Q Liu, Q Dou - IEEE Journal of Biomedical and Health …, 2020 - ieeexplore.ieee.org
The pandemic of coronavirus disease 2019 (COVID-19) has lead to a global public health
crisis spreading hundreds of countries. With the continuous growth of new infections …

A review on deep learning techniques for the diagnosis of novel coronavirus (COVID-19)

MM Islam, F Karray, R Alhajj, J Zeng - Ieee Access, 2021 - ieeexplore.ieee.org
Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world
and has become one of the most acute and severe ailments in the past hundred years. The …

COVID-19 CT image recognition algorithm based on transformer and CNN

X Fan, X Feng, Y Dong, H Hou - Displays, 2022 - Elsevier
Novel corona virus pneumonia (COVID-19) broke out in 2019, which had a great impact on
the development of world economy and people's lives. As a new mainstream image …

Densely connected convolutional networks-based COVID-19 screening model

D Singh, V Kumar, M Kaur - Applied Intelligence, 2021 - Springer
The extensively utilized tool to detect novel coronavirus (COVID-19) is a real-time
polymerase chain reaction (RT-PCR). However, RT-PCR kits are costly and consume critical …

Sounds of COVID-19: exploring realistic performance of audio-based digital testing

J Han, T Xia, D Spathis, E Bondareva, C Brown… - NPJ digital …, 2022 - nature.com
To identify Coronavirus disease (COVID-19) cases efficiently, affordably, and at scale, recent
work has shown how audio (including cough, breathing and voice) based approaches can …

Lung segmentation and automatic detection of COVID-19 using radiomic features from chest CT images

C Zhao, Y Xu, Z He, J Tang, Y Zhang, J Han, Y Shi… - Pattern Recognition, 2021 - Elsevier
This paper aims to develop an automatic method to segment pulmonary parenchyma in
chest CT images and analyze texture features from the segmented pulmonary parenchyma …

Uncertainty-aware semi-supervised method using large unlabeled and limited labeled COVID-19 data

R Alizadehsani, D Sharifrazi, NH Izadi… - ACM Transactions on …, 2021 - dl.acm.org
The new coronavirus has caused more than one million deaths and continues to spread
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …