Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer's disease biomarkers (Aug, 10.1007/s11042-022-13523-6, 2022)

被引：0

作者：

Garg, Gaurav ^{[1
]}

Prasad, Girijesh ^{[2
]}

Garg, Lalit ^{[3
]}

Miyakoshi, Makoto ^{[4
]}

Nakai, Toshiharu ^{[5
]}

Coyle, Damien ^{[2
]}

机构：

[1] BrainAlive Res Pvt Ltd, Embedded Robot, Kanpur, Uttar Pradesh, India

[2] Ulster Univ, Sch Comp & Intelligent Syst, Magee Campus, Coleraine, Londonderry, North Ireland

[3] Univ Malta, Fac Informat & Commun Technol, Msida, Malta

[4] Univ Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, San Diego, CA USA

[5] Natl Ctr Geriatr & Gerontol NCGG, Neuroimaging Informat Lab Niinf, Obu, Japan

来源：

MULTIMEDIA TOOLS AND APPLICATIONS | 2023年 / 82卷 / 06期

关键词：

D O I：

10.1007/s11042-022-13754-7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

引用

页码：9551 / 9552

页数：2

共 41 条

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[34] Classification of Alzheimer's Disease, Mild Cognitive Impairment and Normal Control Subjects Using Resting-State fMRI Based Network Connectivity Analysis
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[36] Network-level permutation entropy of resting-state MEG recordings: A novel biomarker for early-stage Alzheimer's disease? (vol 6, pg 382, 2022)
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[38] Classification of early-MCI patients from healthy controls using evolutionary optimization of graph measures of resting-state fMRI, for the Alzheimer's disease neuroimaging initiative
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[39] Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review (vol 42, pg 2941, 2021)
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[40] Evidence of Neurovascular Un-Coupling in Mild Alzheimer's Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data
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