Tools and techniques for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19 detection

SH Safiabadi Tali, JJ LeBlanc, Z Sadiq… - Clinical microbiology …, 2021 - journals.asm.org
SUMMARY The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute
respiratory disease coronavirus 2 (SARS-CoV-2), has led to millions of confirmed cases and …

U-net and its variants for medical image segmentation: A review of theory and applications

N Siddique, S Paheding, CP Elkin… - IEEE access, 2021 - ieeexplore.ieee.org
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …

Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review

M Khan, MT Mehran, ZU Haq, Z Ullah, SR Naqvi… - Expert systems with …, 2021 - Elsevier
During the current global public health emergency caused by novel coronavirus disease 19
(COVID-19), researchers and medical experts started working day and night to search for …

Comparing machine learning algorithms for predicting COVID-19 mortality

K Moulaei, M Shanbehzadeh… - BMC medical informatics …, 2022 - Springer
Background The coronavirus disease (COVID-19) hospitalized patients are always at risk of
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …

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 …

Efficient deep learning approach for augmented detection of Coronavirus disease

A Sedik, M Hammad, FE Abd El-Samie… - Neural Computing and …, 2022 - Springer
The new Coronavirus disease 2019 (COVID-19) is rapidly affecting the world population
with statistics quickly falling out of date. Due to the limited availability of annotated …

Deep neural network to detect COVID-19: one architecture for both CT Scans and Chest X-rays

H Mukherjee, S Ghosh, A Dhar, SM Obaidullah… - Applied …, 2021 - Springer
Since December 2019, the novel COVID-19's spread rate is exponential, and AI-driven tools
are used to prevent further spreading [1]. They can help predict, screen, and diagnose …

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 …

Deep learning-based meta-classifier approach for COVID-19 classification using CT scan and chest X-ray images

V Ravi, H Narasimhan, C Chakraborty, TD Pham - Multimedia systems, 2022 - Springer
Literature survey shows that convolutional neural network (CNN)-based pretrained models
have been largely used for CoronaVirus Disease 2019 (COVID-19) classification using …

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 …