Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review

A Heidari, NJ Navimipour, M Unal - Sustainable Cities and Society, 2022 - Elsevier
The goal of managing smart cities and societies is to maximize the efficient use of finite
resources while enhancing the quality of life. To establish a sustainable urban existence …

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 …

Machine learning applications for COVID-19 outbreak management

A Heidari, N Jafari Navimipour, M Unal… - Neural Computing and …, 2022 - Springer
Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted
practically every area of human life. Several machine learning (ML) approaches are …

[HTML][HTML] Paradigm shift from Artificial Neural Networks (ANNs) to deep Convolutional Neural Networks (DCNNs) in the field of medical image processing

S Abut, H Okut, KJ Kallail - Expert Systems with Applications, 2024 - Elsevier
Images and other types of unstructural data in the medical domain are rapidly becoming
data-intensive. Actionable insights from these complex data present new opportunities but …

[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 …

Forward layer-wise learning of convolutional neural networks through separation index maximizing

A Karimi, A Kalhor, M Sadeghi Tabrizi - Scientific Reports, 2024 - nature.com
This paper proposes a forward layer-wise learning algorithm for CNNs in classification
problems. The algorithm utilizes the Separation Index (SI) as a supervised complexity …

[HTML][HTML] A systematic review on deep structured learning for COVID-19 screening using chest CT from 2020 to 2022

KC Santosh, D GhoshRoy, S Nakarmi - Healthcare, 2023 - mdpi.com
The emergence of the COVID-19 pandemic in Wuhan in 2019 led to the discovery of a novel
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …

[HTML][HTML] Swin-textural: A novel textural features-based image classification model for COVID-19 detection on chest computed tomography

I Tuncer, PD Barua, S Dogan, M Baygin… - Informatics in Medicine …, 2023 - Elsevier
Background Chest computed tomography (CT) has a high sensitivity for detecting COVID-19
lung involvement and is widely used for diagnosis and disease monitoring. We proposed a …

[HTML][HTML] Evae-net: An ensemble variational autoencoder deep learning network for covid-19 classification based on chest x-ray images

D Addo, S Zhou, JK Jackson, GU Nneji, HN Monday… - Diagnostics, 2022 - mdpi.com
The COVID-19 pandemic has had a significant impact on many lives and the economies of
many countries since late December 2019. Early detection with high accuracy is essential to …

Unraveling complex relationships between COVID-19 risk factors using machine learning based models for predicting mortality of hospitalized patients and …

MM Banoei, H Rafiepoor, K Zendehdel… - Frontiers in …, 2023 - frontiersin.org
Background At the end of 2019, the coronavirus disease 2019 (COVID-19) pandemic
increased the hospital burden of COVID-19 caused by the SARS-Cov-2 and became the …