Adaptive 3DCNN-based Interpretable Ensemble Model for Early Diagnosis of Alzheimer's Disease [0.03%]
基于自适应3DCNN的可解释性集成模型在阿尔茨海默病早期诊断中的应用研究
Dan Pan,Genqiang Luo,An Zeng et al.
Dan Pan et al.
Adaptive interpretable ensemble model based on three-dimensional Convolutional Neural Network (3DCNN) and Genetic Algorithm (GA), i.e., 3DCNN+EL+GA, was proposed to differentiate the subjects with Alzheimer's Disease (AD) or Mild Cognitive ...
Correlation studies of Hippocampal Morphometry and Plasma NFL Levels in Cognitively Unimpaired Subjects [0.03%]
正常认知受试者海马形态学与血浆神经丝轻链水平相关性研究
Qunxi Dong,Zhigang Li,Weijia Liu et al.
Qunxi Dong et al.
Alzheimer's disease(AD) is being the burden of society and family. Applying computing-aided strategies to reveal its pathology is one of the research highlights. Plasma neurofilament light (NFL) is an emerging noninvasive and economic bioma...
Dynamical SEIR Model With Information Entropy Using COVID-19 as a Case Study [0.03%]
基于COVID-19的SEIR模型的信息熵动力学研究
Qi Nie,Yifeng Liu,Dong Zhang et al.
Qi Nie et al.
Social network information is a measure of the number of infections. Understanding the effect of social network information on disease spread can help improve epidemic forecasting and uncover preventive measures. Many driving factors for th...
A Mass-Conservation Model for Stability Analysis and Finite-Time Estimation of Spread of COVID-19 [0.03%]
一个关于COVID-19传播稳定性分析和有限时间估计的守恒模型
Hossein Rastgoftar,Ella Atkins
Hossein Rastgoftar
The COVID-19 global pandemic has significantly impacted people throughout the United States and the World. While it was initially believed the virus was transmitted from animal to human, person-to-person transmission is now recognized as th...
Detecting Community Depression Dynamics Due to COVID-19 Pandemic in Australia [0.03%]
澳大利亚新冠疫情下的社区抑郁动态监测
Jianlong Zhou,Hamad Zogan,Shuiqiao Yang et al.
Jianlong Zhou et al.
The recent Coronavirus Infectious Disease 2019 (COVID-19) pandemic has caused an unprecedented impact across the globe. We have also witnessed millions of people with increased mental health issues, such as depression, stress, worry, fear, ...
Muhammad Iqbal,Feras Al-Obeidat,Fahad Maqbool et al.
Muhammad Iqbal et al.
In December 2019, a pandemic named COVID-19 broke out in Wuhan, China, and in a few weeks, it spread to more than 200 countries worldwide. Every country infected with the disease started taking necessary measures to stop the spread and prov...
Sentiment Analysis of Lockdown in India During COVID-19: A Case Study on Twitter [0.03%]
新冠肺炎期间印度封锁的社会情绪分析：一项关于Twitter的实证研究
Prasoon Gupta,Sanjay Kumar,R R Suman et al.
Prasoon Gupta et al.
With the rapid increase in the use of the Internet, sentiment analysis has become one of the most popular fields of natural language processing (NLP). Using sentiment analysis, the implied emotion in the text can be mined effectively for di...
Maximilian Vierlboeck,Roshanak Rose Nilchiani,Christine M Edwards
Maximilian Vierlboeck
When it comes to pandemics, such as the one caused by the Coronavirus disease COVID-19, various issues and problems have arisen for the healthcare infrastructure and institutions. With increasing number of patients in need of urgent medical...
COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis [0.03%]
用于COVID-19情感分析的大型基准推特数据集
Usman Naseem,Imran Razzak,Matloob Khushi et al.
Usman Naseem et al.
Social media (and the world at large) have been awash with news of the COVID-19 pandemic. With the passage of time, news and awareness about COVID-19 spread like the pandemic itself, with an explosion of messages, updates, videos, and posts...
Ranking of Importance Measures of Tweet Communities: Application to Keyword Extraction From COVID-19 Tweets in Japan [0.03%]
基于日本Covid-19推特的关键词抽取的重要度排名措施研究
Ryosuke Harakawa,Masahiro Iwahashi
Ryosuke Harakawa
This article presents a method that detects tweet communities with similar topics and ranks the communities by importance measures. By identifying the tweet communities that have high importance measures, it is possible for users to easily ...