[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 …

Transfer learning techniques for medical image analysis: A review

P Kora, CP Ooi, O Faust, U Raghavendra… - Biocybernetics and …, 2022 - Elsevier
Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …

[HTML][HTML] A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images

MZ Islam, MM Islam, A Asraf - Informatics in medicine unlocked, 2020 - Elsevier
Nowadays, automatic disease detection has become a crucial issue in medical science due
to rapid population growth. An automatic disease detection framework assists doctors in the …

Automated medical diagnosis of COVID-19 through EfficientNet convolutional neural network

G Marques, D Agarwal, I De la Torre Díez - Applied soft computing, 2020 - Elsevier
COVID-19 infection was reported in December 2019 at Wuhan, China. This virus critically
affects several countries such as the USA, Brazil, India and Italy. Numerous research units …

CNN-based transfer learning–BiLSTM network: A novel approach for COVID-19 infection detection

MF Aslan, MF Unlersen, K Sabanci, A Durdu - Applied Soft Computing, 2021 - Elsevier
Abstract Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019
and has spread rapidly all over the world since the beginning of 2020, has infected millions …

A deep learning approach to detect Covid-19 coronavirus with X-Ray images

G Jain, D Mittal, D Thakur, MK Mittal - Biocybernetics and biomedical …, 2020 - Elsevier
Rapid and accurate detection of COVID-19 coronavirus is necessity of time to prevent and
control of this pandemic by timely quarantine and medical treatment in absence of any …

FINE_DENSEIGANET: Automatic medical image classification in chest CT scan using Hybrid Deep Learning Framework

HP Sahu, R Kashyap - International Journal of Image and Graphics, 2025 - World Scientific
Medical image classification is one of the most significant tasks in computer-aided
diagnosis. In the era of modern healthcare, the progress of digitalized medical images has …

IoT enabled depthwise separable convolution neural network with deep support vector machine for COVID-19 diagnosis and classification

DN Le, VS Parvathy, D Gupta, A Khanna… - International journal of …, 2021 - Springer
At present times, the drastic advancements in the 5G cellular and internet of things (IoT)
technologies find useful in different applications of the healthcare sector. At the same time …

Complex features extraction with deep learning model for the detection of COVID19 from CT scan images using ensemble based machine learning approach

MR Islam, M Nahiduzzaman - Expert Systems with Applications, 2022 - Elsevier
Recently the most infectious disease is the novel Coronavirus disease (COVID 19) creates a
devastating effect on public health in more than 200 countries in the world. Since the …

A deep transfer learning-based convolution neural network model for COVID-19 detection using computed tomography scan images for medical applications

ND Kathamuthu, S Subramaniam, QH Le… - … in Engineering Software, 2023 - Elsevier
Abstract The Coronavirus (COVID-19) has become a critical and extreme epidemic because
of its international dissemination. COVID-19 is the world's most serious health, economic …