[HTML][HTML] 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 …

[HTML][HTML] Compressing medical deep neural network models for edge devices using knowledge distillation

FME Alabbasy, AS Abohamama… - Journal of King Saud …, 2023 - Elsevier
Recently, deep neural networks (DNNs) have been used successfully in many fields,
particularly, in medical diagnosis. However, deep learning (DL) models are expensive in …

Attention induced multi-head convolutional neural network organization with MobileNetv1 transfer learning and COVID-19 diagnosis using jellyfish search …

M Ramkumar, MS Gowtham, SS Jamaesha… - … Signal Processing and …, 2024 - Elsevier
Abstract In this research, Attention Induced Multi-head Convolutional Neural Network
Organization using MobileNetv1 Transfer Learning and COVID-19 Diagnosis using Jellyfish …

Machine learning and deep learning algorithms in detecting COVID-19 utilizing medical images: a comprehensive review

Nurjahan, M Mahbub-Or-Rashid, MS Satu… - Iran Journal of Computer …, 2024 - Springer
The public's health is seriously at risk from the coronavirus pandemic. Millions of people
have already died as a result of this devastating illness, which affects countless people daily …

TfrAdmCov: a robust transformer encoder based model with Adam optimizer algorithm for COVID-19 mutation prediction

M Burukanli, N Yumuşak - Connection Science, 2024 - Taylor & Francis
The development of vaccines and drugs is very important in combating the coronavirus
disease 2019 (COVID-19) virus. The effectiveness of these developed vaccines and drugs …

[HTML][HTML] An intelligent garment for long COVID-19 real-time monitoring

MJ Nkengue, X Zeng, L Koehl, X Tao… - Computers in Biology …, 2024 - Elsevier
As monitoring and diagnostic tools for long COVID-19 cases, wearable systems and
supervised learning-based medical image analysis have proven to be useful. Current …

A novel soft computing based efficient feature selection approach for timely identification of COVID-19 infection using chest computed tomography images: a human …

LK Singh, M Khanna, H Garg, R Singh - Multimedia Tools and …, 2024 - Springer
The SARS-CoV-2 coronavirus strain's introduction in December 2019 resulted in the
development of the new coronavirus disease, COVID-19. Following its first appearance, the …

Intelligent computing framework to analyze the transmission risk of COVID-19: Meyer wavelet artificial neural networks

KS Nisar, I Naz, MAZ Raja, M Shoaib - Computational Biology and …, 2024 - Elsevier
The optimum control methods for the epidemiology of the COVID-19 model are
acknowledged using a novel advanced intelligent computing infrastructure that joins artificial …

Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network

R Prince, Z Niu, ZY Khan, J Chambua, A Yousif… - Computers in Biology …, 2025 - Elsevier
Deep learning methods have significantly improved medical image analysis, particularly in
detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some …

Compressing medical deep neural network models for edge devices using knowledge distillation

F MohiEldeen Alabbasy, AS Abohamama… - 2023 - dl.acm.org
Recently, deep neural networks (DNNs) have been used successfully in many fields,
particularly, in medical diagnosis. However, deep learning (DL) models are expensive in …