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 …

An overview of deep learning techniques for COVID-19 detection: methods, challenges, and future works

E Gürsoy, Y Kaya - Multimedia Systems, 2023 - Springer
Abstract The World Health Organization (WHO) declared a pandemic in response to the
coronavirus COVID-19 in 2020, which resulted in numerous deaths worldwide. Although the …

The economics of deep and machine learning-based algorithms for COVID-19 prediction, detection, and diagnosis sha** the organizational management of …

G Lăzăroiu, T Gedeon, E Rogalska… - Oeconomia …, 2024 - cejsh.icm.edu.pl
Research background: Deep and machine learning-based algorithms can assist in COVID-
19 image-based medical diagnosis and symptom tracing, optimize intensive care unit …

Authentication schemes for healthcare applications using wireless medical sensor networks: A survey

AN Bahache, N Chikouche, F Mezrag - SN Computer Science, 2022 - Springer
Many applications are developed with the quick emergence of the Internet of things (IoT)
and wireless sensor networks (WSNs) in the health sector. Healthcare applications that use …

[HTML][HTML] Internet of things with deep learning techniques for pandemic detection: A comprehensive review of current trends and open issues

SA Ajagbe, P Mudali, MO Adigun - Electronics, 2024 - mdpi.com
Technological advancements for diverse aspects of life have been made possible by the
swift development and application of Internet of Things (IoT) based technologies. IoT …

[HTML][HTML] A novel hybrid supervised and unsupervised hierarchical ensemble for COVID-19 cases and mortality prediction

V Yakovyna, N Shakhovska, A Szpakowska - Scientific Reports, 2024 - nature.com
Though COVID-19 is no longer a pandemic but rather an endemic, the epidemiological
situation related to the SARS-CoV-2 virus is develo** at an alarming rate, impacting every …

Digital transformation process towards resilient production systems and networks

D Mourtzis, N Panopoulos - Supply network dynamics and control, 2022 - Springer
Coordinating the digital transformation of globally dispersed factories within global
manufacturing networks has become critical for competitiveness. From the procurement of …

Application of artificial intelligence in assessing the self-management practices of patients with type 2 diabetes

RM Ansari, MF Harris, H Hosseinzadeh, N Zwar - Healthcare, 2023 - mdpi.com
The use of Artificial intelligence in healthcare has evolved substantially in recent years. In
medical diagnosis, Artificial intelligence algorithms are used to forecast or diagnose a …

An assessment of ensemble learning approaches and single-based machine learning algorithms for the characterization of undersaturated oil viscosity

TT Akano, CC James - Beni-Suef University Journal of Basic and Applied …, 2022 - Springer
Background Prediction of accurate crude oil viscosity when pressure volume temperature
(PVT) experimental results are not readily available has been a major challenge to the …

Performance of machine learning models for pandemic detection using COVID-19 dataset

SA Ajagbe, AA Adegun, P Mudali… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
The pandemic produced by coronavirus2 (COVID-19) and other related infectious diseases
have been confined to the world, and there is a need to control its spread as well as prepare …