An effective detection of COVID-19 using adaptive dual-stage horse herd bidirectional long short-term memory framework [0.03%]
一种使用自适应双阶段马群双向长短期记忆框架有效检测COVID-19的方法
Durga Prasad Mannepalli,Varsha Namdeo
Durga Prasad Mannepalli
COVID-19 is a quickly increasing severe viral disease that affects the human beings as well as animals. The increasing amount of infection and death due to COVID-19 needs timely detection. This work presented an innovative deep learning met...
CoviDetNet: A new COVID-19 diagnostic system based on deep features of chest x-ray [0.03%]
基于胸部X光片深度特征的新的冠状病毒诊断系统(CoviDetNet)
Muzaffer Aslan
Muzaffer Aslan
COVID-19 has emerged as a global pandemic affecting the world, and its adverse effects on society still continue. So far, about 243.57 million people have been diagnosed with COVID-19, of which about 4.94 million have died. In this study, a...
COVID-opt-aiNet: A clinical decision support system for COVID-19 detection [0.03%]
一种针对新型冠状病毒肺炎检测的临床决策支持系统COVID-opt-aiNetBarkeley APACHE IV: Development and validation of a machine learning severity-of illness model to predict in-hospital mortality for adults
Summrina Kanwal,Faiza Khan,Sultan Alamri et al.
Summrina Kanwal et al.
Coronavirus disease (COVID-19) has had a major and sometimes lethal effect on global public health. COVID-19 detection is a difficult task that necessitates the use of intelligent diagnosis algorithms. Numerous studies have suggested the us...
Detection and diagnosis of COVID-19 infection in lungs images using deep learning techniques [0.03%]
基于深度学习技术的肺部CT图像新冠肺炎检测与诊断
Arun Kumar,Rajendra Prasad Mahapatra
Arun Kumar
World's science and technologies have been challenged by the COVID-19 pandemic. Each and every community across the globe are trying to find a real-time novel method for accurate treatment and cure of COVID-19 infected patients. The most im...
A lightweight capsule network architecture for detection of COVID-19 from lung CT scans [0.03%]
一种轻量级的用于从肺部CT图像中检测COVID-19的胶囊网络架构
Shamik Tiwari,Anurag Jain
Shamik Tiwari
COVID-19, a novel coronavirus, has spread quickly and produced a worldwide respiratory ailment outbreak. There is a need for large-scale screening to prevent the spreading of the disease. When compared with the reverse transcription polymer...
Can laboratory parameters be an alternative to CT and RT-PCR in the diagnosis of COVID-19? A machine learning approach [0.03%]
基于机器学习的参数在新冠肺炎诊断中的作用可替代CT和核酸检测吗？
Mehmet Kalaycı,Hakan Ayyıldız,Seda Arslan Tuncer et al.
Mehmet Kalaycı et al.
In this study, a machine learning-based decision support system that uses routine laboratory parameters has been proposed in order to increase the diagnostic success in COVID-19. The main goal of the proposed method was to reduce the number...
Multimodal covid network: Multimodal bespoke convolutional neural network architectures for COVID-19 detection from chest X-ray's and computerized tomography scans [0.03%]
用于从胸部X光和计算机断层扫描图像中检测COVID-19的多模态自适应卷积神经网络架构
Thiyagarajan Padmapriya,Thiruvenkatam Kalaiselvi,Venugopal Priyadharshini
Thiyagarajan Padmapriya
AI-based tools were developed in the existing works, which focused on one type of image data; either CXR's or computerized tomography (CT) scans for COVID-19 prediction. There is a need for an AI-based tool that predicts COVID-19 detection ...
Automatic classification of severity of COVID-19 patients using texture feature and random forest based on computed tomography images [0.03%]
基于CT图像利用纹理特征和随机森林自动分类COVID-19患者的病情严重程度
Nasrin Amini,Ahmad Shalbaf
Nasrin Amini
Severity assessment of the novel Coronavirus (COVID-19) using chest computed tomography (CT) scan is crucial for the effective administration of the right therapeutic drugs and also for monitoring the progression of the disease. However, de...
Randomly initialized convolutional neural network for the recognition of COVID-19 using X-ray images [0.03%]
使用X光图像识别COVID-19的随机初始化卷积神经网络
Safa Ben Atitallah,Maha Driss,Wadii Boulila et al.
Safa Ben Atitallah et al.
By the start of 2020, the novel coronavirus (COVID-19) had been declared a worldwide pandemic, and because of its infectiousness and severity, several strands of research have focused on combatting its ongoing spread. One potential solution...
The effect of deep feature concatenation in the classification problem: An approach on COVID-19 disease detection [0.03%]
深度特征拼接在分类问题中的影响：一种针对COVID-19疾病检测的方法
Emine Cengil,Ahmet Çınar
Emine Cengil
In image classification applications, the most important thing is to obtain useful features. Convolutional neural networks automatically learn the extracted features during training. The classification process is carried out with the obtain...