Automated detection and forecasting of covid-19 using deep learning techniques: A review
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 …
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 …
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …
Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …
Ensemble deep learning and internet of things‐based automated COVID‐19 diagnosis framework
AS Kini, AN Gopal Reddy, M Kaur… - Contrast Media & …, 2022 - Wiley Online Library
Coronavirus disease (COVID‐19) is a viral infection caused by SARS‐CoV‐2. The
modalities such as computed tomography (CT) have been successfully utilized for the early …
modalities such as computed tomography (CT) have been successfully utilized for the early …
NAGNN: classification of COVID‐19 based on neighboring aware representation from deep graph neural network
COVID‐19 pneumonia started in December 2019 and caused large casualties and huge
economic losses. In this study, we intended to develop a computer‐aided diagnosis system …
economic losses. In this study, we intended to develop a computer‐aided diagnosis system …
A new approach for computer-aided detection of coronavirus (COVID-19) from CT and X-ray images using machine learning methods
A Saygılı - Applied Soft Computing, 2021 - Elsevier
The COVID-19 outbreak has been causing a global health crisis since December 2019. Due
to this virus declared by the World Health Organization as a pandemic, the health authorities …
to this virus declared by the World Health Organization as a pandemic, the health authorities …
Detection of COVID-19 severity using blood gas analysis parameters and Harris hawks optimized extreme learning machine
J Hu, AA Heidari, Y Shou, H Ye, L Wang… - Computers in Biology …, 2022 - Elsevier
Abstract Coronavirus disease-2019 (COVID-19) has made the world more cautious about
widespread viruses, and a tragic pandemic that was caused by a novel coronavirus has …
widespread viruses, and a tragic pandemic that was caused by a novel coronavirus has …
xViTCOS: explainable vision transformer based COVID-19 screening using radiography
Objective: Since its outbreak, the rapid spread of COrona VIrus Disease 2019 (COVID-19)
across the globe has pushed the health care system in many countries to the verge of …
across the globe has pushed the health care system in many countries to the verge of …
Multi-surrogate assisted binary particle swarm optimization algorithm and its application for feature selection
The evolutionary algorithms (EAs) have been shown favorable performance for feature
selection. However, a large number of evaluations are required through the EAs. Thus, they …
selection. However, a large number of evaluations are required through the EAs. Thus, they …
Multigraph fusion for dynamic graph convolutional network
Graph convolutional network (GCN) outputs powerful representation by considering the
structure information of the data to conduct representation learning, but its robustness is …
structure information of the data to conduct representation learning, but its robustness is …