COVID-19 detection based on pre-trained deep networks and LSTM model using X-ray images enhanced contrast with artificial bee colony algorithm [0.03%]
基于预训练深度网络和LSTM模型的COVID-19检测方法(使用人工蜂群算法增强X光图像对比度)
Mehmet Bilal Er
Mehmet Bilal Er
Coronavirus (COVID-19) is an infectious disease that has spread across the world within a short period of time and is causing rapid casualties. The main symptoms of this virus are shortness of breath, fever, cough, and a sore throat. The vi...
Deepraj Chowdhury,Soham Banerjee,Madhushree Sannigrahi et al.
Deepraj Chowdhury et al.
The world is affected by COVID-19, an infectious disease caused by the SARS-CoV-2 virus. Tests are necessary for everyone as the number of COVID-19 affected individual's increases. So, the authors developed a basic sequential CNN model base...
Models for MAGDM with dual hesitant q-rung orthopair fuzzy 2-tuple linguistic MSM operators and their application to COVID-19 pandemic [0.03%]
基于双犹豫q-正交直项语言MSM算子的COVID-19大流行多属性群决策模型研究
Sumera Naz,Muhammad Akram,Arsham Borumand Saeid et al.
Sumera Naz et al.
In this article, we introduce dual hesitant q -rung orthopair fuzzy 2-tuple linguistic set (DHq-ROFTLS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into dual hesitant q -rung orthopair fuzz...
Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods [0.03%]
基于贝叶斯超参数优化和深度特征选择方法的COVID-19及其肺部分期检测
Nedim Muzoğlu,Ahmet Mesrur Halefoğlu,Muhammed Onur Avci et al.
Nedim Muzoğlu et al.
Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful...
Artificial neural networks for prediction of COVID-19 in India by using backpropagation [0.03%]
印度利用反向传播预测COVID-19的人工神经网络方法
Balakrishnama Manohar,Raja Das
Balakrishnama Manohar
The COVID-19 pandemic has affected thousands of people around the world. In this study, we used artificial neural network (ANN) models to forecast the COVID-19 outbreak for policymakers based on 1st January to 31st October 2021 of positive ...
Detection of COVID-19 from chest X-ray images: Boosting the performance with convolutional neural network and transfer learning [0.03%]
基于卷积神经网络和迁移学习的COVID-19胸部X光图像检测方法研究
Sohaib Asif,Yi Wenhui,Kamran Amjad et al.
Sohaib Asif et al.
Coronavirus disease (COVID-19) is a pandemic that has caused thousands of casualties and impacts all over the world. Most countries are facing a shortage of COVID-19 test kits in hospitals due to the daily increase in the number of cases. E...
Effective hybrid deep learning model for COVID-19 patterns identification using CT images [0.03%]
基于CT图像的有效混合深度学习模型用于识别新冠肺炎征候
Dheyaa Ahmed Ibrahim,Dilovan Asaad Zebari,Hussam J Mohammed et al.
Dheyaa Ahmed Ibrahim et al.
Coronavirus disease 2019 (COVID-19) has attracted significant attention of researchers from various disciplines since the end of 2019. Although the global epidemic situation is stabilizing due to vaccination, new COVID-19 cases are constant...
Covid-19 cases prediction using SARIMAX Model by tuning hyperparameter through grid search cross-validation approach [0.03%]
基于网格搜索交叉验证的SARIMAX模型的超参数调优及COVID-19病例预测研究
Sweeti Sah,Balasubramanian Surendiran,Ramasamy Dhanalakshmi et al.
Sweeti Sah et al.
SARS-Coronavirus was first detected in December 2019, later named COVID-19, and declared a pandemic by the World Health Organization (WHO). As prediction models assist policymakers in making decisions based on expected outcomes. Existing mo...
COVID-19 special issue: Intelligent solutions for computer communication-assisted infectious disease diagnosis [0.03%]
新冠肺炎专题：基于计算机通信辅助的智能传染病诊断方法
Fadi Al-Turjman
Fadi Al-Turjman
Masood Ghayoomi,Maryam Mousavian
Masood Ghayoomi
The spread of fake news on social media has increased dramatically in recent years. Hence, fake news detection systems have received researchers' attention globally. During the COVID-19 outbreak in 2019 and the worldwide epidemic, the impor...