COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network

T Rahman, A Akinbi, MEH Chowdhury… - … Information Science and …, 2022 - Springer
The reliable and rapid identification of the COVID-19 has become crucial to prevent the
rapid spread of the disease, ease lockdown restrictions and reduce pressure on public …

Carbon nanopores for DNA sequencing: a review on nanopore materials

J Xu, X Jiang, N Yang - Chemical Communications, 2023 - pubs.rsc.org
In the past few decades, nanometer-scale pores have been employed as a powerful tool for
sensing biological molecules. In pursuit of this technology, a variety of nanotechnology …

Viral diseases and the environment relationship

CG do Amaral, EP André, EM Cilli, VG da Costa… - Environmental …, 2024 - Elsevier
Viral diseases have been present throughout human history, with early examples including
influenza (1500 BC), smallpox (1000 BC), and measles (200 BC). The term" virus" was first …

Diabetic retinopathy improved detection using deep learning

A Ayala, T Ortiz Figueroa, B Fernandes, F Cruz - Applied Sciences, 2021 - mdpi.com
Diabetes is a disease that occurs when the body presents an uncontrolled level of glucose
that is capable of damaging the retina, leading to permanent damage of the eyes or vision …

MXT: A new variant of pyramid vision transformer for multi-label chest X-ray image classification

X Jiang, Y Zhu, G Cai, B Zheng, D Yang - Cognitive Computation, 2022 - Springer
Nowadays, the global COVID-19 situation is still serious, and the new mutant virus Delta has
already spread all over the world. The chest X-ray is one of the most common radiological …

A hybrid deep learning approach for COVID-19 detection based on genomic image processing techniques

MS Hammad, VF Ghoneim, MS Mabrouk… - Scientific Reports, 2023 - nature.com
Abstract The coronavirus disease 2019 (COVID-19) pandemic has been spreading quickly,
threatening the public health system. Consequently, positive COVID-19 cases must be …

[PDF][PDF] DNN-GFE: a deep neural network model combined with global feature extractor for COVID-19 diagnosis based on CT scan images

JH Joloudari, F Azizi, I Nodehi, MA Nematollahi… - Easychair …, 2021 - easychair.org
Materials and Methods: Hence, a Deep Neural Network model combined with a Global
Feature Extractor called DNNGFE is proposed for COVID-19 diagnosis with 1252 sick and …

A novel unsupervised approach based on the hidden features of Deep Denoising Autoencoders for COVID-19 disease detection

M Scarpiniti, SS Ahrabi, E Baccarelli, L Piazzo… - Expert Systems with …, 2022 - Elsevier
Chest imaging can represent a powerful tool for detecting the Coronavirus disease 2019
(COVID-19). Among the available technologies, the chest Computed Tomography (CT) scan …

Identification and classification of coronavirus genomic signals based on linear predictive coding and machine learning methods

A Khodaei, P Shams, H Sharifi… - … Signal Processing and …, 2023 - Elsevier
Corona disease has become one of the problems and challenges of humankind over the
past two years. One of the problems that existed from the first days of this epidemic was …

Technical trends in public healthcare and medical engineering

AR Mishra, A Rai, MD Ansari… - Privacy Preservation of …, 2023 - Wiley Online Library
Healthcare is a sizable sector of the economy with outdated systems, which can result in
inefficiencies. For healthcare and associated purposes, use computing platforms …