ECG-COVID: An end-to-end deep model based on electrocardiogram for COVID-19 detection [0.03%]
ECG-COVID：用于COVID-19检测基于心电图的端到端深度模型
Ahmed S Sakr,Paweł Pławiak,Ryszard Tadeusiewicz et al.
Ahmed S Sakr et al.
The early and accurate detection of COVID-19 is vital nowadays to avoid the vast and rapid spread of this virus and ease lockdown restrictions. As a result, researchers developed methods to diagnose COVID-19. However, these methods have sev...
An integrated interval-valued intuitionistic fuzzy technique for resumption risk assessment amid COVID-19 prevention [0.03%]
COVID-19预防期间的恢复风险评估的区间值直觉模糊技术集成方法
Ze-Hui Chen,Shu-Ping Wan,Jiu-Ying Dong
Ze-Hui Chen
Currently, China has achieved a remarkable achievement on the containment of COVID-19, which creates a favorable condition for the gradual resumption of normal life. However, COVID-19 infections continue to rise in many nations and some spo...
Francesco Buccafurri,Vincenzo De Angelis,Cecilia Labrini
Francesco Buccafurri
Digital contact tracing (DCT) is one of the weapons to be used against the COVID-19 pandemic, especially in a post-lockdown phase, to prevent or block foci of infection. As DCT systems can handle highly private information about people, gre...
An efficient deep neural network framework for COVID-19 lung infection segmentation [0.03%]
一种高效的深度神经网络框架实现新型冠状病毒肺炎肺部感染灶的快速精确定位与分割
Ge Jin,Chuancai Liu,Xu Chen
Ge Jin
Since the outbreak of Coronavirus Disease 2019 (COVID-19) in 2020, it has significantly affected the global health system. The use of deep learning technology to automatically segment pneumonia lesions from Computed Tomography (CT) images c...
Outperformance of the pharmaceutical sector during the COVID-19 pandemic: Global time-varying screening rule development [0.03%]
新冠疫情下的制药业超额收益：全球时间变化筛选规则制定
Carlos Esparcia,Raquel López
Carlos Esparcia
This study demonstrates the major role played by the healthcare and pharmaceutical industries during the COVID-19 pandemic. For this purpose, it provides evidence of a better risk-return relationship in these sectors through a multivariate ...
GFCNet: Utilizing graph feature collection networks for coronavirus knowledge graph embeddings [0.03%]
利用图特征集合网络进行冠状病毒知识图谱嵌入(GFCNet)
Zhiwen Xie,Runjie Zhu,Jin Liu et al.
Zhiwen Xie et al.
In response to fighting COVID-19 pandemic, researchers in machine learning and artificial intelligence have constructed some medical knowledge graphs (KG) based on existing COVID-19 datasets, however, these KGs contain a considerable amount...
Coronavirus fake news detection via MedOSINT check in health care official bulletins with CBR explanation: The way to find the real information source through OSINT, the verifier tool for official journals [0.03%]
基于CBR解释的新型冠状病毒假新闻检测：通过MedOSINT核查卫生行政部门公告查找真实信息来源及官方期刊验证工具
Sergio Mauricio Martinez Monterrubio,Amaya Noain-Sánchez,Elena Verdú Pérez et al.
Sergio Mauricio Martinez Monterrubio et al.
This research aims to design and prototype a tool to perform intelligence on open sources (OSINT), specifically on official medical bulletins for the detection of false news. MedOSINT is a modular tool that can be adapted to process informa...
Estimating unconfirmed COVID-19 infection cases and multiple waves of pandemic progression with consideration of testing capacity and non-pharmaceutical interventions: A dynamic spreading model [0.03%]
考虑检测能力和非药物干预措施的COVID-19未确认感染病例及疫情多波动态传播模型估算研究
Choujun Zhan,Lujiao Shao,Xinyu Zhang et al.
Choujun Zhan et al.
The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has unique epidemiological characteristics that include presymptomatic and asymptomatic infections, resulting in a large ...
Interval nonlinear initial-valued problem using constraint intervals: Theory and an application to the Sars-Cov-2 outbreak [0.03%]
约束区间下的非线性初值问题的理论及应用——以SARS-CoV-2疫情为例
M S Cecconello,M T Mizukoshi,W Lodwick
M S Cecconello
This article discusses the theory of constraint interval solutions to interval nonlinear initial value problems and applies the notion of constraint interval solutions to analyze the asymptotic behavior of a susceptible-infected-recovered (...
RCTE: A reliable and consistent temporal-ensembling framework for semi-supervised segmentation of COVID-19 lesions [0.03%]
RCTE：用于半监督分割COVID-19病变的可靠且一致的时间集成框架
Weiping Ding,Mohamed Abdel-Basset,Hossam Hawash
Weiping Ding
The segmentation of COVID-19 lesions from computed tomography (CT) scans is crucial to develop an efficient automated diagnosis system. Deep learning (DL) has shown success in different segmentation tasks. However, an efficient DL approach ...