[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 …
Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review
During the current global public health emergency caused by novel coronavirus disease 19
(COVID-19), researchers and medical experts started working day and night to search for …
(COVID-19), researchers and medical experts started working day and night to search for …
Design and analysis of a deep learning ensemble framework model for the detection of COVID-19 and pneumonia using large-scale CT scan and X-ray image …
Recently, various methods have been developed to identify COVID-19 cases, such as PCR
testing and non-contact procedures such as chest X-rays and computed tomography (CT) …
testing and non-contact procedures such as chest X-rays and computed tomography (CT) …
Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and …
A viral outbreak is a global challenge that affects public health and safety. The coronavirus
disease 2019 (COVID-19) has been spreading globally, affecting millions of people …
disease 2019 (COVID-19) has been spreading globally, affecting millions of people …
Ear recognition based on deep unsupervised active learning
Y Khaldi, A Benzaoui, A Ouahabi… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Cooperative machine learning has many applications, such as data annotation, where an
initial model trained with partially labeled data is used to predict labels for unseen data …
initial model trained with partially labeled data is used to predict labels for unseen data …
Cvd-hnet: Classifying pneumonia and Covid-19 in chest x-ray images using deep network
S Suganyadevi, V Seethalakshmi - Wireless Personal Communications, 2022 - Springer
The use of computer-assisted analysis to improve image interpretation has been a long-
standing challenge in the medical imaging industry. In terms of image comprehension …
standing challenge in the medical imaging industry. In terms of image comprehension …
Generative adversarial network based data augmentation for CNN based detection of Covid-19
Covid-19 has been a global concern since 2019, crippling the world economy and health.
Biological diagnostic tools have since been developed to identify the virus from bodily fluids …
Biological diagnostic tools have since been developed to identify the virus from bodily fluids …
A framework for efficient brain tumor classification using MRI images
A brain tumor is an abnormal growth of brain cells inside the head, which reduces the
patient's survival chance if it is not diagnosed at an earlier stage. Brain tumors vary in size …
patient's survival chance if it is not diagnosed at an earlier stage. Brain tumors vary in size …
A machine learning method for the quantitative detection of adulterated meat using a MOS-based E-nose
C Huang, Y Gu - Foods, 2022 - mdpi.com
Meat adulteration is a global problem which undermines market fairness and harms people
with allergies or certain religious beliefs. In this study, a novel framework in which a one …
with allergies or certain religious beliefs. In this study, a novel framework in which a one …
Rapid diagnosis of Covid-19 infections by a progressively growing GAN and CNN optimisation
Background and objective Covid-19 infections are spreading around the globe since
December 2019. Several diagnostic methods were developed based on biological …
December 2019. Several diagnostic methods were developed based on biological …