Classification of Alzheimer's disease and mild cognitive impairment: Machine learning applied to rs-fMRI brain graphs

2016 23rd Iranian Conference on Biomedical Engineering and 2016 1st International Iranian Conference on Biomedical Engineering (ICBME) ◽

10.1109/icbme.2016.7890925 ◽

2016 ◽

Cited By ~ 1

Author(s):

Soroosh Golbabaei ◽

Amirali Vahid ◽

Javad Hatami ◽

Hamid Soltanian-Zadeh

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment

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Machine Learning classification of MRI features of Alzheimer's disease and mild cognitive impairment subjects to reduce the sample size in clinical trials

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.2011.6091962 ◽

2011 ◽

Cited By ~ 4

Author(s):

J. Escudero ◽

J. P. Zajicek ◽

E. Ifeachor

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Clinical Trials ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Sample Size ◽

Machine Learning Classification ◽

Mri Features

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Using Machine Learning to Differentiate between Healthy Aging, Mild Cognitive Impairment, & Alzheimer's Disease

10.17918/d8th5x ◽

2021 ◽

Author(s):

Monica Truelove-Hill

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Healthy Aging

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Classification of Alzheimer's disease and mild cognitive impairment by pattern recognition of EEG power and coherence

2010 IEEE International Conference on Acoustics, Speech and Signal Processing ◽

10.1109/icassp.2010.5495193 ◽

2010 ◽

Cited By ~ 8

Author(s):

Kwaku Akrofi ◽

Ranadip Pal ◽

Mary C. Baker ◽

Brian S. Nutter ◽

Randolph W. Schiffer

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Pattern Recognition ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Eeg Power

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Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Cognitively Normal Based on Neuropsychological Data via Supervised Learning

TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON) ◽

10.1109/tencon.2019.8929443 ◽

2019 ◽

Author(s):

Gwo Giun Lee ◽

Po-Wei Huang ◽

Yi-Ru Xie ◽

Ming-Chyi Pai

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Supervised Learning ◽

Cognitively Normal

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A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures

Frontiers in Neurology ◽

10.3389/fneur.2019.00756 ◽

2019 ◽

Vol 10 ◽

Cited By ~ 6

Author(s):

Massimiliano Grassi ◽

Nadine Rouleaux ◽

Daniela Caldirola ◽

David Loewenstein ◽

Koen Schruers ◽

...

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Learning Algorithm ◽

Clinical Information ◽

Demographic Characteristics ◽

Machine Learning Algorithm ◽

Neuropsychological Measures

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A machine learning-based linguistic battery for diagnosing mild cognitive impairment due to Alzheimer’s disease

PLoS ONE ◽

10.1371/journal.pone.0229460 ◽

2020 ◽

Vol 15 (3) ◽

pp. e0229460

Author(s):

Sylvester Olubolu Orimaye ◽

Karl Goodkin ◽

Ossama Abid Riaz ◽

Jean-Maurice Miranda Salcedo ◽

Thabit Al-Khateeb ◽

...

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment

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Ensemble Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Complex Graph Measures from Diffusion Tensor Images

Frontiers in Neuroscience ◽

10.3389/fnins.2017.00056 ◽

2017 ◽

Vol 11 ◽

Cited By ~ 17

Author(s):

Ashkan Ebadi ◽

Josué L. Dalboni da Rocha ◽

Dushyanth B. Nagaraju ◽

Fernanda Tovar-Moll ◽

Ivanei Bramati ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Diffusion Tensor ◽

Ensemble Classification ◽

Complex Graph ◽

Diffusion Tensor Images

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Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer’s disease

Brain Imaging and Behavior ◽

10.1007/s11682-015-9448-7 ◽

2015 ◽

Vol 10 (3) ◽

pp. 799-817 ◽

Cited By ~ 86

Author(s):

Ali Khazaee ◽

Ata Ebrahimzadeh ◽

Abbas Babajani-Feremi

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Resting State ◽

Resting State Fmri ◽

Learning Methods ◽

Machine Learning Methods

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Comparative accuracies of two common screening instruments for classification of Alzheimer's disease, mild cognitive impairment, and healthy aging

Alzheimer s & Dementia ◽

10.1016/j.jalz.2012.10.001 ◽

2012 ◽

Vol 9 (5) ◽

pp. 529-537 ◽

Cited By ~ 138

Author(s):

David R. Roalf ◽

Paul J. Moberg ◽

Sharon X. Xie ◽

David A. Wolk ◽

Stephen T. Moelter ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Healthy Aging ◽

Screening Instruments

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Classification of Alzheimer’s Disease, Mild Cognitive Impairment, and Normal Controls with Multilayer Perceptron Neural Network and Neuropsychological Test Data

Proceedings of the 12th International Joint Conference on Computational Intelligence ◽

10.5220/0010143304390446 ◽

2020 ◽

Cited By ~ 1

Author(s):

Ibrahim Almubark ◽

Samah Alsegehy ◽

Xiong Jiang ◽

Lin-Ching Chang

Keyword(s):

Neural Network ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Test Data ◽

Multilayer Perceptron ◽

Neuropsychological Test ◽

Normal Controls

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