Analysis of Alzheimer's Disease Based on the Random Neural Network Cluster in fMRI

Frontiers in Neuroinformatics
Xia-An BiYingchao Liu

Abstract

As Alzheimer's disease (AD) is featured with degeneration and irreversibility, the diagnosis of AD at early stage is important. In recent years, some researchers have tried to apply neural network (NN) to classify AD patients from healthy controls (HC) based on functional MRI (fMRI) data. But most study focus on a single NN and the classification accuracy was not high. Therefore, this paper used the random neural network cluster which was composed of multiple NNs to improve classification performance. Sixty one subjects (25 AD and 36 HC) were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. This method not only could be used in the classification, but also could be used for feature selection. Firstly, we chose Elman NN from five types of NNs as the optimal base classifier of random neural network cluster based on the results of feature selection, and the accuracies of the random Elman neural network cluster could reach to 92.31% which was the highest and stable. Then we used the random Elman neural network cluster to select significant features and these features could be used to find out the abnormal regions. Finally, we found out 23 abnormal regions such as the precentral gyrus, the frontal gyrus ...Continue Reading

References

Jan 1, 1993·Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism·K J FristonR S Frackowiak
Jan 1, 1997·Brain : a Journal of Neurology·T A YousryP Winkler
Jan 23, 2003·Brain : a Journal of Neurology·Murray GrossmanUNKNOWN fMRI study. Functional magnetic resonance imaging
Apr 9, 2004·Proceedings of the National Academy of Sciences of the United States of America·Michael D GreiciusVinod Menon
Feb 12, 2005·Brain : a Journal of Neurology·Alexandra GolbyJohn Gabrieli
Oct 26, 2005·NeuroImage·Ronald McKell CarterRaymond J Dolan
Sep 21, 2006·Brain : a Journal of Neurology·Foucaud du BoisgueheneucBruno Dubois
Jun 26, 2010·Frontiers in Systems Neuroscience·Yan Chao-Gan, Zang Yu-Feng
Aug 5, 2011·Neurobiology of Aging·Federica AgostaMassimo Filippi
Aug 25, 2011·Neurobiology of Aging·Maja A A BinnewijzendFrederik Barkhof
Nov 3, 2012·Human Brain Mapping·Mary Beth NebelStewart H Mostofsky
Aug 14, 2013·Journal of the Neurological Sciences·Kyunghun KangHo-Won Lee
Jul 22, 2014·NeuroImage·Heung-Il SukUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Oct 15, 2014·NeuroImage·Elaheh MoradiUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Apr 25, 2015·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·Ali KhazaeeAbbas Babajani-Feremi
Aug 21, 2015·BMC Neurology·Marjolein M A EngelsElisabeth C W van Straaten
Oct 1, 2015·Journal of Medical Systems·Thomas J HirschauerJohn A Buford
Mar 10, 2016·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·Ian T Jolliffe, Jorge Cadima
Mar 10, 2016·IEEE Transactions on Medical Imaging·Marios AnthimopoulosStavroula Mougiakakou
Jun 1, 2016·Frontiers in Human Neuroscience·Marjolein M A EngelsElisabeth C W van Straaten
Aug 2, 2016·International Journal of Neural Systems·Andrés OrtizJavier Ramírez
Nov 26, 2016·Computer Methods and Programs in Biomedicine·Xiaohong W GaoZengmin Tian
Dec 7, 2016·Dementia and Geriatric Cognitive Disorders Extra·Ludovica GriffantiGiovanna Zamboni
Jul 1, 2017·European Journal of Nuclear Medicine and Molecular Imaging·Marco PaganiFabrizio De Carli

❮ Previous
Next ❯

Citations

Jul 18, 2020·Reviews in the Neurosciences·Jalal MirakhorliMojgan Mirakhorli
Feb 14, 2020·Current Alzheimer Research·Zhongke GaoUNKNOWN Alzheimer’s DiseaseNeuroimaging Initiative
Dec 30, 2018·Journal of Neuroscience Methods·Parisa ForouzannezhadMalek Adjouadi

❮ Previous
Next ❯

Methods Mentioned

BETA
feature extraction

Software Mentioned

Brain
Data Processing Assistant for Resting - State fMRI ( DPARSF )
NetViewer
PreCG

Related Concepts

Related Feeds

Alzheimer's Disease: Neuroimaging

Neuroimaging can help identify pathological hallmarks of Alzheimer's disease (AD). Here is the latest research on neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, in AD.