Hemodynamic functional connectivity optimization of frequency EEG microstates enables attention LSTM framework to classify distinct temporal cortical communications of different cognitive tasks [0.03%]
基于频率的EEG微状态的血流动力学功能连接优化使注意力LSTM框架能够分类不同认知任务的不同时间皮层通信
Swati Agrawal,Vijayakumar Chinnadurai,Rinku Sharma
Swati Agrawal
Temporal analysis of global cortical communication of cognitive tasks in coarse EEG information is still challenging due to the underlying complex neural mechanisms. This study proposes an attention-based time-series deep learning framework...
Machine learning methods for the study of cybersickness: a systematic review [0.03%]
机器学习方法在网络空间恶心感的研究中的应用：系统性综述
Alexander Hui Xiang Yang,Nikola Kasabov,Yusuf Ozgur Cakmak
Alexander Hui Xiang Yang
This systematic review offers a world-first critical analysis of machine learning methods and systems, along with future directions for the study of cybersickness induced by virtual reality (VR). VR is becoming increasingly popular and is a...
Early detection of Alzheimer's disease using neuropsychological tests: a predict-diagnose approach using neural networks [0.03%]
基于神经网络的预测诊断方法在阿尔茨海默病早期检测中的应用研究
Devarshi Mukherji,Manibrata Mukherji,Nivedita Mukherji;Alzheimer’s Disease Neuroimaging Initiative
Devarshi Mukherji
Alzheimer's disease (AD) is a slowly progressing disease for which there is no known therapeutic cure at present. Ongoing research around the world is actively engaged in the quest for identifying markers that can help predict the future co...
Jamal Nazari,Ali Motie Nasrabadi,Mohammad Bagher Menhaj et al.
Jamal Nazari et al.
Epileptic seizures prediction and timely alarms allow the patient to take effective and preventive actions. In this paper, a convolutional neural network (CNN) is proposed to diagnose the preictal period. Our goal is for those epileptic pat...
Kostas Georgiadis,Fotis P Kalaganis,Vangelis P Oikonomou et al.
Kostas Georgiadis et al.
Neuromarketing exploits neuroimaging techniques so as to reinforce the predictive power of conventional marketing tools, like questionnaires and focus groups. Electroencephalography (EEG) is the most commonly encountered neuroimaging techni...
A multi-expert ensemble system for predicting Alzheimer transition using clinical features [0.03%]
基于临床特征的阿尔茨海默病多专家预测系统
Mario Merone,Sebastian Luca D&#x;Addario,Pierandrea Mirino et al.
Mario Merone et al.
Alzheimer's disease (AD) diagnosis often requires invasive examinations (e.g., liquor analyses), expensive tools (e.g., brain imaging) and highly specialized personnel. The diagnosis commonly is established when the disorder has already cau...
ABOT: an open-source online benchmarking tool for machine learning-based artefact detection and removal methods from neuronal signals [0.03%]
ABOT：一种用于基于机器学习的神经信号伪迹检测和移除方法的在线开放工具
Marcos Fabietti,Mufti Mahmud,Ahmad Lotfi et al.
Marcos Fabietti et al.
Brain signals are recorded using different techniques to aid an accurate understanding of brain function and to treat its disorders. Untargeted internal and external sources contaminate the acquired signals during the recording process. Oft...
SmaRT2P: a software for generating and processing smart line recording trajectories for population two-photon calcium imaging [0.03%]
智能线记录轨迹生成和处理的软件SmaRT2P用于人群双光子钙成像
Monica Moroni,Marco Brondi,Tommaso Fellin et al.
Monica Moroni et al.
Two-photon fluorescence calcium imaging allows recording the activity of large neural populations with subcellular spatial resolution, but it is typically characterized by low signal-to-noise ratio (SNR) and poor accuracy in detecting singl...
A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer's Disease [0.03%]
一种稳健的框架，用于研究轻度认知障碍和阿尔茨海默病的可解释人工智能标记的可靠性和稳定性
Angela Lombardi,Domenico Diacono,Nicola Amoroso et al.
Angela Lombardi et al.
In clinical practice, several standardized neuropsychological tests have been designed to assess and monitor the neurocognitive status of patients with neurodegenerative diseases such as Alzheimer's disease. Important research efforts have ...
Machine learning-based ABA treatment recommendation and personalization for autism spectrum disorder: an exploratory study [0.03%]
基于机器学习的自闭症谱系障碍ABA治疗推荐和个人化的探索性研究
Manu Kohli,Arpan Kumar Kar,Anjali Bangalore et al.
Manu Kohli et al.
Autism spectrum is a brain development condition that impairs an individual's capacity to communicate socially and manifests through strict routines and obsessive-compulsive behavior. Applied behavior analysis (ABA) is the gold-standard tre...