Diagnosing COVID-19 using artificial intelligence: A comprehensive review

VV Khanna, K Chadaga, N Sampathila… - … Modeling Analysis in …, 2022 - Springer
Abstract In early March 2020, the World Health Organization (WHO) proclaimed the novel
COVID-19 as a global pandemic. The coronavirus went on to be a life-threatening infection …

A deep transfer learning-based convolution neural network model for COVID-19 detection using computed tomography scan images for medical applications

ND Kathamuthu, S Subramaniam, QH Le… - … in Engineering Software, 2023 - Elsevier
Abstract The Coronavirus (COVID-19) has become a critical and extreme epidemic because
of its international dissemination. COVID-19 is the world's most serious health, economic …

[HTML][HTML] Advances in artificial intelligence for accurate and timely diagnosis of COVID-19: A comprehensive review of medical imaging analysis

YEI El-Bouzaidi, O Abdoun - Scientific African, 2023 - Elsevier
In December 2019, the first case of coronavirus 2019 (COVID-19) appeared in China,
quickly leading to a global pandemic. Early and accurate diagnosis is crucial for effective …

Deep learning models-based CT-scan image classification for automated screening of COVID-19

K Gupta, V Bajaj - Biomedical Signal Processing and Control, 2023 - Elsevier
COVID-19 is the most transmissible disease, caused by the SARS-CoV-2 virus that severely
infects the lungs and the upper respiratory tract of the human body. This virus badly affected …

A comprehensive review of machine learning used to combat COVID-19

R Gomes, C Kamrowski, J Langlois, P Rozario, I Dircks… - Diagnostics, 2022 - mdpi.com
Coronavirus disease (COVID-19) has had a significant impact on global health since the
start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed …

COVID-19 Image Classification: A Comparative Performance Analysis of Hand-Crafted vs. Deep Features

S Alinsaif - Computation, 2024 - mdpi.com
This study investigates techniques for medical image classification, specifically focusing on
COVID-19 scans obtained through computer tomography (CT). Firstly, handcrafted methods …

A fuzzy fine-tuned model for COVID-19 diagnosis

N Esmi, Y Golshan, S Asadi, A Shahbahrami… - Computers in biology …, 2023 - Elsevier
The COVID-19 disease pandemic spread rapidly worldwide and caused extensive human
death and financial losses. Therefore, finding accurate, accessible, and inexpensive …

A Space Infrared Dim Target Recognition Algorithm Based on Improved DS Theory and Multi-Dimensional Feature Decision Level Fusion Ensemble Classifier

X Chen, H Zhang, S Zhang, J Feng, H Xia, P Rao, J Ai - Remote Sensing, 2024 - mdpi.com
Space infrared dim target recognition is an important applications of space situational
awareness (SSA). Due to the weak observability and lack of geometric texture of the target, it …

OzNet: A new deep learning approach for automated classification of COVID-19 computed tomography scans

O Ozaltin, O Yeniay, A Subasi - Big data, 2023 - liebertpub.com
Coronavirus disease 2019 (COVID-19) is spreading rapidly around the world. Therefore, the
classification of computed tomography (CT) scans alleviates the workload of experts, whose …

A user-friendly AI-based clinical decision support system for rapid detection of pandemic diseases:: Covid-19 and Monkeypox

T Adar, EK Delice, O Delice - Journal of Intelligent & Fuzzy Systems, 2024 - dl.acm.org
Accurate and rapid diagnosis is a significant factor in reducing incidence rate; especially
when the number of people inflicted with a disease is considerably high. In the healthcare …