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 …
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
Neural Networks for the Detection of COVID-19 and Other Diseases: Prospects and Challenges
M Azeem, S Javaid, RA Khalil, H Fahim, T Althobaiti… - Bioengineering, 2023 - mdpi.com
Artificial neural networks (ANNs) ability to learn, correct errors, and transform a large amount
of raw data into beneficial medical decisions for treatment and care has increased in …
of raw data into beneficial medical decisions for treatment and care has increased in …
Real‑time COVID-19 diagnosis from X-Ray images using deep CNN and extreme learning machines stabilized by chimp optimization algorithm
T Hu, M Khishe, M Mohammadi, GR Parvizi… - … Signal Processing and …, 2021 - Elsevier
Real-time detection of COVID-19 using radiological images has gained priority due to the
increasing demand for fast diagnosis of COVID-19 cases. This paper introduces a novel two …
increasing demand for fast diagnosis of COVID-19 cases. This paper introduces a novel two …
Automated detection of COVID-19 from CT scan using convolutional neural network
Under the prevailing circumstances of the global pandemic of COVID-19, early diagnosis
and accurate detection of COVID-19 through tests/screening and, subsequently, isolation of …
and accurate detection of COVID-19 through tests/screening and, subsequently, isolation of …
Remotely monitoring COVID-19 patient health condition using metaheuristics convolute networks from IoT-based wearable device health data
Today, COVID-19-patient health monitoring and management are major public health
challenges for technologies. This research monitored COVID-19 patients by using the …
challenges for technologies. This research monitored COVID-19 patients by using the …
[HTML][HTML] A novel explainable COVID-19 diagnosis method by integration of feature selection with random forest
M Rostami, M Oussalah - Informatics in Medicine Unlocked, 2022 - Elsevier
Abstract Several Artificial Intelligence-based models have been developed for COVID-19
disease diagnosis. In spite of the promise of artificial intelligence, there are very few models …
disease diagnosis. In spite of the promise of artificial intelligence, there are very few models …
COVID-19 diagnosis from routine blood tests using artificial intelligence techniques
Abstract Coronavirus disease (COVID-19) is a unique worldwide pandemic. With new
mutations of the virus with higher transmission rates, it is imperative to diagnose positive …
mutations of the virus with higher transmission rates, it is imperative to diagnose positive …
An ensemble learning model for COVID-19 detection from blood test samples
OO Abayomi-Alli, R Damaševičius, R Maskeliūnas… - Sensors, 2022 - mdpi.com
Current research endeavors in the application of artificial intelligence (AI) methods in the
diagnosis of the COVID-19 disease has proven indispensable with very promising results …
diagnosis of the COVID-19 disease has proven indispensable with very promising results …
ADU-Net: an attention dense U-Net based deep supervised DNN for automated lesion segmentation of COVID-19 from chest CT images
An automatic method for qualitative and quantitative evaluation of chest Computed
Tomography (CT) images is essential for diagnosing COVID-19 patients. We aim to develop …
Tomography (CT) images is essential for diagnosing COVID-19 patients. We aim to develop …
A novel fusion based convolutional neural network approach for classification of COVID-19 from chest X-ray images
Coronavirus disease is a viral infection caused by a novel coronavirus (CoV) which was first
identified in the city of Wuhan, China somewhere in the early December 2019. It affects the …
identified in the city of Wuhan, China somewhere in the early December 2019. It affects the …