TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification [0.03%]
TSCMamba：时间序列分类中的多视图学习方法
Md Atik Ahamed,Qiang Cheng
Md Atik Ahamed
Multivariate time series classification (TSC) is critical for various applications in fields such as healthcare and finance. While various approaches for TSC have been explored, important properties of time series, such as shift equivarianc...
NAPS Fusion: A framework to overcome experimental data limitations to predict human performance and cognitive task outcomes [0.03%]
融合框架以克服实验数据限制预测人类表现及认知任务结果
Nicholas J Napoli,Chad L Stephens,Kellie D Kennedy et al.
Nicholas J Napoli et al.
In the area of human performance and cognitive research, machine learning (ML) problems become increasingly complex due to limitations in the experimental design, resulting in the development of poor predictive models. More specifically, ex...
UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection [0.03%]
基于集成蒙特卡洛 dropout 的不确定性和层次特征融合模型用于新冠肺炎检测
Moloud Abdar,Soorena Salari,Sina Qahremani et al.
Moloud Abdar et al.
The COVID-19 (Coronavirus disease 2019) pandemic has become a major global threat to human health and well-being. Thus, the development of computer-aided detection (CAD) systems that are capable of accurately distinguishing COVID-19 from ot...
SPICE-IT: Smart COVID-19 pandemic controlled eradication over NDN-IoT [0.03%]
基于NDN-IoT的智能COVID-19大流行控制消除技术
Muhammad Toaha Raza Khan,Malik Muhammad Saad,Muhammad Ashar Tariq et al.
Muhammad Toaha Raza Khan et al.
Internet of things (IoT) application in e-health can play a vital role in countering rapidly spreading diseases that can effectively manage health emergency scenarios like pandemics. Efficient disease control also requires monitoring of Sta...
Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions [0.03%]
数字医疗中的信息融合的数据规范化：系统性回顾、元分析及未来研究方向
Yang Nan,Javier Del Ser,Simon Walsh et al.
Yang Nan et al.
Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and proto...
Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond [0.03%]
基于多模态和多中心数据融合的医学可解释AI研究：迷你综述、两个实例及展望
Guang Yang,Qinghao Ye,Jun Xia
Guang Yang
Explainable Artificial Intelligence (XAI) is an emerging research topic of machine learning aimed at unboxing how AI systems' black-box choices are made. This research field inspects the measures and models involved in decision-making and s...
Diagnosis of multiple sclerosis using multifocal ERG data feature fusion [0.03%]
多焦ERG数据特征融合在多发性硬化诊断中的应用
A López-Dorado,J Pérez,M J Rodrigo et al.
A López-Dorado et al.
The purpose of this paper is to implement a computer-aided diagnosis (CAD) system for multiple sclerosis (MS) based on analysing the outer retina as assessed by multifocal electroretinograms (mfERGs). MfERG recordings taken with the RETI-po...
Editorial: Advances in multi-source information fusion for epidemic diseases [0.03%]
编者按：传染病多源信息融合研究新进展
Yin Zhang,Ala Al-Fuqaha,Iztok Humar et al.
Yin Zhang et al.
Pay attention to doctor-patient dialogues: Multi-modal knowledge graph attention image-text embedding for COVID-19 diagnosis [0.03%]
关注医患对话：用于COVID-19诊断的多模态知识图注意图文嵌入方法
Wenbo Zheng,Lan Yan,Chao Gou et al.
Wenbo Zheng et al.
The sudden increase in coronavirus disease 2019 (COVID-19) cases puts high pressure on healthcare services worldwide. At this stage, fast, accurate, and early clinical assessment of the disease severity is vital. In general, there are two i...
A critic evaluation of methods for COVID-19 automatic detection from X-ray images [0.03%]
基于X射线图像的新冠肺炎自动检测方法评述
Gianluca Maguolo,Loris Nanni
Gianluca Maguolo
In this paper, we compare and evaluate different testing protocols used for automatic COVID-19 diagnosis from X-Ray images in the recent literature. We show that similar results can be obtained using X-Ray images that do not contain most of...