[HTML][HTML] Review of COVID-19 testing and diagnostic methods
O Filchakova, D Dossym, A Ilyas, T Kuanysheva… - Talanta, 2022 - Elsevier
More than six billion tests for COVID-19 has been already performed in the world. The
testing for SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) virus and …
testing for SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) virus and …
Application of artificial intelligence in wearable devices: Opportunities and challenges
D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …
problems for people with a detrimental effect on the functioning of the nervous system. In …
[HTML][HTML] Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods
The first known case of Coronavirus disease 2019 (COVID-19) was identified in December
2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and …
2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and …
Combining a convolutional neural network with autoencoders to predict the survival chance of COVID-19 patients
COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus
is highly desired. Convolutional neural networks (CNNs) have shown outstanding …
is highly desired. Convolutional neural networks (CNNs) have shown outstanding …
A novel approach for diabetic retinopathy screening using asymmetric deep learning features
Automatic screening of diabetic retinopathy (DR) is a well-identified area of research in the
domain of computer vision. It is challenging due to structural complexity and a marginal …
domain of computer vision. It is challenging due to structural complexity and a marginal …
Application of CycleGAN and transfer learning techniques for automated detection of COVID-19 using X-ray images
Coronavirus (which is also known as COVID-19) is severely impacting the wellness and
lives of many across the globe. There are several methods currently to detect and monitor …
lives of many across the globe. There are several methods currently to detect and monitor …
Uncertainty-aware semi-supervised method using large unlabeled and limited labeled COVID-19 data
R Alizadehsani, D Sharifrazi, NH Izadi… - ACM Transactions on …, 2021 - dl.acm.org
The new coronavirus has caused more than one million deaths and continues to spread
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
RADIC: A tool for diagnosing COVID-19 from chest CT and X-ray scans using deep learning and quad-radiomics
O Attallah - Chemometrics and Intelligent Laboratory Systems, 2023 - Elsevier
Deep learning (DL) algorithms have demonstrated a high ability to perform speedy and
accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The …
accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The …