Automated detection and forecasting of covid-19 using deep learning techniques: A review
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 …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function
Recent studies have shown that computed tomography (CT) scan images can characterize
COVID-19 disease in patients. Several deep learning (DL) methods have been proposed for …
COVID-19 disease in patients. Several deep learning (DL) methods have been proposed for …
A hybrid random forest deep learning classifier empowered edge cloud architecture for COVID-19 and pneumonia detection
M Hemalatha - Expert Systems with Applications, 2022 - Elsevier
COVID-19 is a global pandemic that mostly affects patients' respiratory systems, and the only
way to protect oneself against the virus at present moment is to diagnose the illness, isolate …
way to protect oneself against the virus at present moment is to diagnose the illness, isolate …
Applying a deep residual network coupling with transfer learning for recyclable waste sorting
Recyclable waste sorting has become a key step for promoting the development of a circular
economy with the gradual realization of carbon neutrality around the world. This study aims …
economy with the gradual realization of carbon neutrality around the world. This study aims …
DCML: Deep contrastive mutual learning for COVID-19 recognition
H Zhang, W Liang, C Li, Q Xiong, H Shi, L Hu… - … Signal Processing and …, 2022 - Elsevier
COVID-19 is a form of disease triggered by a new strain of coronavirus. Automatic COVID-19
recognition using computer-aided methods is beneficial for speeding up diagnosis …
recognition using computer-aided methods is beneficial for speeding up diagnosis …
A multimodal AI-based non-invasive COVID-19 grading framework powered by deep learning, manta ray, and fuzzy inference system from multimedia vital signs
SA Almutairi - Heliyon, 2023 - cell.com
The COVID-19 pandemic has presented unprecedented challenges to healthcare systems
worldwide. One of the key challenges in controlling and managing the pandemic is accurate …
worldwide. One of the key challenges in controlling and managing the pandemic is accurate …
[HTML][HTML] Deep learning attention-guided radiomics for COVID-19 chest radiograph classification
Background Accurate assessment of coronavirus disease 2019 (COVID-19) lung
involvement through chest radiograph plays an important role in effective management of …
involvement through chest radiograph plays an important role in effective management of …
Dynamic Chest Radiograph Simulation Technique with Deep Convolutional Neural Networks: A Proof-of-Concept Study
Simple Summary Dynamic chest radiographs offer a distinct advantage over traditional chest
radiographs by integrating motion and functional data, elevating their significance in clinical …
radiographs by integrating motion and functional data, elevating their significance in clinical …
A deep learning model for diagnosing COVID-19 and pneumonia through X-ray
Background: The new global pandemic caused by the 2019 novel coronavirus (COVID-19),
novel coronavirus pneumonia, has spread rapidly around the world, causing enormous …
novel coronavirus pneumonia, has spread rapidly around the world, causing enormous …
[PDF][PDF] Enhanced Disease Detection Using Contrast Limited Adaptive Histogram Equalization and Multi-Objective Cuckoo Search in Deep Learning
Accepted: 5 May 2023 Delayed diagnosis of numerous diseases often results in postponed
treatment, adversely affecting patient outcomes. By analyzing biological signals and patient …
treatment, adversely affecting patient outcomes. By analyzing biological signals and patient …