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Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI

Edward Challis, Peter Hurley, Laura Serra, Marco Bozzali, Seb Oliver, Mara Cercignani
2015 NeuroImage  
amnesic mild cognitive impairment and 97% accuracy disambiguating amnesic mild cognitive impairment subjects from those with Alzheimer's disease, accuracies are estimated using a held-out test set.  ...  Researchers and clinicians are also increasingly interested in the study of functional-connectivity patterns of brains at rest and how these relations might change in conditions like Alzheimer's disease  ...  Acknowlegments This work was supported by the Science and Technology Facilities Council [ST/K002279/1]  ... 
doi:10.1016/j.neuroimage.2015.02.037 pmid:25731993 fatcat:l6wlvv73gjc7xpa4ibz3e63ehi

A list of publications describing new supervised learning pipelines to predict clinical variables from neuroimaging data in Alzheimer's disease

Alex F Mendelson
2016 Figshare  
This is a list of publications describing new classification and regression methods to predict clinical variables relevant to Alzheimer's disease using neurological images.  ...  Oliver, and M. Cercignani. Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI. Neuroimage, 112:232-243, 2015. [48] R. Chaves, J. Górriz, J.  ...  Antuono, and S.-J. Li. Classification of Alzheimer disease, mild cognitive impairment, and normal cognitive status with large-scale network analysis based on resting-state functional MR imaging.  ... 
doi:10.6084/m9.figshare.3435752 fatcat:mdtfbkinjzfezcg6qhhwx43s4e

Classifying early and late mild cognitive impairment stages of Alzheimer's disease by fusing default mode networks extracted with multiple seeds

Shengbing Pei, Jihong Guan, Shuigeng Zhou
2018 BMC Bioinformatics  
In the study, we used 18 early mild cognitive impairment (EMCI) participants and 18 late mild cognitive impairment (LMCI) participants of Alzheimer's disease (AD).  ...  The default mode network (DMN) in resting state has been increasingly used in disease diagnosis since it was found in 2001.  ...  We test this idea on a data set consisting of early mild cognitive impairment participants (EMCI) and late mild cognitive impairment participants (LMCI) of Alzheimer's disease [26] [27] [28] .  ... 
doi:10.1186/s12859-018-2528-0 fatcat:7o6sk5w3rbarfawn2kz3m65jym

MALINI (Machine Learning in NeuroImaging): A MATLAB toolbox for aiding clinical diagnostics using resting-state fMRI data

Pradyumna Lanka, D. Rangaprakash, Sai Sheshan Roy Gotoor, Michael N. Dretsch, Jeffrey S. Katz, Thomas S. Denney, Gopikrishna Deshpande
2020 Data in Brief  
spectrum disorder from autism brain imaging data exchange (ABIDE), Alzheimer's disease and mild cognitive impairment from Alzheimer's disease neuroimaging initiative (ADNI), attention deficit hyperactivity  ...  Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has been extensively used for diagnostic classification because it does not require task compliance and is easier to pool data from multiple  ...  We used the LIBSVM package [29] for the implementation of support vector machine (SVM) in MATLAB https://www.csie.ntu.edu.tw/~cjlin/libsvm.  ... 
doi:10.1016/j.dib.2020.105213 pmid:32090157 pmcid:PMC7025186 fatcat:xskpsiap3fccdjdczlij7dyrtq

Regions and Sub-regions Dysfunctions in Alzheimer's during Rest

K. C. Usha Usha, Dr. H. N. Suma
2020 Asian Journal of Medicine and Health  
We employ the most potential resting-state functional Magnetic Resonance Imaging (rs-fMRI) modality for this analysis.  ...  Methodology: 24 Alzheimer's disease (AD) and 25 Healthy Controlled (HC) subjects were evaluated with rs-fMRI which is more efficient in anticipating neuronal activity changes.  ...  PMCID: PMC5432635 Available:http:Selective functional connectivity of the hippocampus changes of resting-state Altered directed in mild cognitive impairment and Alzheimer's disease: A resting-state fMRI  ... 
doi:10.9734/ajmah/2020/v18i530205 fatcat:el23vgr6kvg7nmmbiohxinlepi

Advances in Resting State Neuroimaging of Mild Cognitive Impairment

Li Lin, Guoqiang Xing, Ying Han
2018 Frontiers in Psychiatry  
Mild cognitive impairment (MCI), characterized with accelerated memory decline than normal aging, is a stage between cognitively unimpaired and dementia.  ...  Secondly, we cover studies that use of rs-fMRI (resting state functional magnetic resonance imaging) for the brain activities and functional connectivity between normal aging and MCI.  ...  Also, the authors would like to thank the staff from the Center of Alzheimer's Disease of the Beijing Institute for Brain Disorders and everyone else who helped out with various issues.  ... 
doi:10.3389/fpsyt.2018.00671 pmid:30574100 pmcid:PMC6291484 fatcat:ankmqth4qnbf5b2fctf2mr63cm

Disrupted functional connectivity between perirhinal and parahippocampal cortices with hippocampal subfields in patients with mild cognitive impairment and Alzheimer's disease

Yu Sun, Yafei Wang, Jiaming Lu, Rengyuan Liu, Christopher G. Schwarz, Hui Zhao, Yue Zhang, Lingyi Xu, Bin Zhu, Bing Zhang, Bing Liu, Suiren Wan (+1 others)
2017 OncoTarget  
Most patients with mild cognitive impairment and Alzheimer's disease can initially present memory loss.  ...  , n=31) and Alzheimer's disease (AD group, n=27) was investigated in this study.  ...  Mild cognitive impairment (MCI) has been seen as a prodromal stage of AD [1] .  ... 
doi:10.18632/oncotarget.17944 pmid:29228757 pmcid:PMC5716797 fatcat:wleyb6esczfpxliwfb4hurlcaq

Regional Homogeneity in Patients With Mild Cognitive Impairment: A Resting-State Functional Magnetic Resonance Imaging Study

Yu-Qian Wu, Yi-Ning Wang, Li-Juan Zhang, Li-Qi Liu, Yi-Cong Pan, Ting Su, Xu-Lin Liao, Hui-Ye Shu, Min Kang, Ping Ying, San-Hua Xu, Yi Shao
2022 Frontiers in Aging Neuroscience  
cognitive impairment in patients with pre- Alzheimer's disease may be related to the excitation and inhibition of neural networks in these regions.  ...  ObjectiveTo analyze the potential changes in brain neural networks in resting state functional magnetic resonance imaging (rs-fMRI) scans by regional homogeneity (ReHo) in patients with mild cognitive  ...  H-YS, MK, PY, and S-HX collected the data. YS conceived, designed and directed the study, and final revised and approved the manuscript.  ... 
doi:10.3389/fnagi.2022.877281 pmid:35493938 pmcid:PMC9050296 fatcat:ukvpj5gwpzhvtgbedtkiujbzsm

Evolutionary optimization in classification of early-MCI patients from healthy controls using graph measures of resting-state fMRI [article]

Jafar Zamani, Ali Sadr, Amir-Homayoun Javadi
2021 bioRxiv   pre-print
Identifying individuals with early mild cognitive impairment (EMCI) can be an effective strategy for early diagnosis and delay the progression of Alzheimer's disease (AD).  ...  Resting-state functional magnetic resonance imaging (rs-fMRI) measures, which measure functional connectivity, have been shown to be useful in prediction of cognitive decline.  ...  JZ and AHJ analyzed the data. JZ and AHJ wrote the paper. JZ, AS and AHJ revised the manuscript. AS and AHJ supervised the project.  ... 
doi:10.1101/2021.03.04.433989 fatcat:k3vv2wezbnay5fibpl4q32hfka

Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients: a resting-state functional magnetic resonance imaging study

Ting Li, Zhengluan Liao, Yanping Mao, Jiaojiao Hu, Dansheng Le, Yangliu Pei, Wangdi Sun, Jixin Lin, Yaju Qiu, Junpeng Zhu, Yan Chen, Chang Qi (+3 others)
2021 Annals of Translational Medicine  
in patients with AD or mild cognitive impairment (MCI).  ...  Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory impairment.  ...  AD, Alzheimer's Disease; MCI, mild cognitive impairment; HC, healthy controls; MMSE, Mini-mental State Examination; MoCA, Montreal Cognitive Assessment.  ... 
doi:10.21037/atm-20-7214 pmid:33553356 pmcid:PMC7859807 fatcat:mgrlabszajef3i34dgf23w4ikq

Density-based clustering of static and dynamic functional MRI connectivity features obtained from subjects with cognitive impairment

D. Rangaprakash, Alzheimer's Disease Neuroimaging Initiative, Toluwanimi Odemuyiwa, D. Narayana Dutt, Gopikrishna Deshpande
2020 Brain Informatics  
AbstractVarious machine-learning classification techniques have been employed previously to classify brain states in healthy and disease populations using functional magnetic resonance imaging (fMRI).  ...  Alzheimer's disease.  ...  Acknowledgements Data used in this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu).  ... 
doi:10.1186/s40708-020-00120-2 pmid:33242116 fatcat:ciw3vscdjzf7jflpm2r4snn54q

Diagnosis of Alzheimer's Disease Severity with fMRI Images Using Robust Multitask Feature Extraction Method and Convolutional Neural Network (CNN)

Morteza Amini, MirMohsen Pedram, AliReza Moradi, Mahshad Ouchani
2021 Computational and Mathematical Methods in Medicine  
The severity is also calculated based on the Mini-Mental State Examination score, including low, mild, moderate, and severe categories.  ...  Based on the findings, the presented CNN architecture classifier outperforms other methods and can diagnose the severity and stages of Alzheimer's disease with maximum accuracy.  ...  Conflicts of Interest The authors declare that there are no financial or other conflicts of interest in this research and its publication.  ... 
doi:10.1155/2021/5514839 pmid:34007305 pmcid:PMC8100410 fatcat:zcw4oa76rbbktddmsygegdvr5q

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

Xia-an Bi, Qin Jiang, Qi Sun, Qing Shu, Yingchao Liu
2018 Frontiers in Neuroinformatics  
., and Cercignani, M. (2015). Gaussian process classification of Alzheimer’s disease and mild cognitive impairment from resting-state fMRI.  ...  Resting-state fMRI changes in Alzheimer’s disease and mild cognitive impairment. Neurobiol.  ... 
doi:10.3389/fninf.2018.00060 pmid:30245623 pmcid:PMC6137384 fatcat:nh4lnlttnrbszcv2qp2ouqtkim

Alterations of the default mode network and cognitive impairments in patients with chronic obstructive pulmonary disease

Hu XW, Wang HB, Tu YH, Fei MD, Yin MM, Fei GH, Yu YQ
2018 International Journal of COPD  
Keywords: chronic obstructive pulmonary disease, cognitive function, resting state f [...]  ...  All participants performed cognitive function tests and underwent resting state functional magnetic resonance imaging.Results: The total cognitive function scores of COPD patients were significantly different  ...  Disease and the brain’s dark energy. Zhang HY, Wang SJ, Xing J, et al. Detection of PCC functional connectivity characteristics in resting-state fMRI in mild Alzheimer’s disease.  ... 
doaj:7992174fdd614d4d9b6fa7ba1f76c5d9 fatcat:7rp2s4xiy5ayhh5thm2cdvmlia

Altered Regional Cerebral Blood Flow and Brain Function Across the Alzheimer's Disease Spectrum: A Potential Biomarker

Qianqian Zhang, Qing Wang, Cancan He, Dandan Fan, Yao Zhu, Feifei Zang, Chang Tan, Shaoke Zhang, Hao Shu, Zhijun Zhang, Haixia Feng, Zan Wang (+1 others)
2021 Frontiers in Aging Neuroscience  
).Methods: The study recruited 20 individuals in each of the following categories: Alzheimer's disease (AD), mild cognitive impairment (MCI), subjective cognitive decline (SCD), and healthy control (HC  ...  All participants completed the 3.0T resting-state functional MRI (rs-fMRI) and arterial spin labeling scans in addition to neuropsychological tests.  ...  HC, Healthy Control; SCD, Subjective Cognitive Decline; MCI, Mild Cognitive Impairment; AD, Alzheimer's Disease; F/M, Female/Male; MMSE, Mini-Mental State Examination; ADL, Activities of Daily Living;  ... 
doi:10.3389/fnagi.2021.630382 pmid:33692680 pmcid:PMC7937726 fatcat:ogf7v6u5zffhrdcpp2fqexkka4
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