Diagnosis of Alzheimer's disease and Mild Cognitive Impairment using EEG and Recurrent Neural Networks-Reference-Cited by-同舟云学术

Diagnosis of Alzheimer's disease and Mild Cognitive Impairment using EEG and Recurrent Neural Networks

Published:2022-07-11 Issue: Volume: Page:
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Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Gkenios Georgios¹,Latsiou Konstantina¹,Diamantaras Konstantinos²,Chouvarda Ioanna³,Tsolaki Magda⁴

Affiliation:

1. School of Science and Technology, International Hellenic University,Thermi,Thessaloniki,Greece,57001

2. International Hellenic University,Department of Information and Electronic Engineering,Sindos,Thessaloniki,Greece,57400

3. School of Medicine, Aristotle University of Thessaloniki,Lab of Computing Medical Informatics and Biomedical Imaging Technologies,Thessaloniki,Greece,54124

4. Greek Association of Alzheimer's Disease and Related Disorders,Thessaloniki,Greece,54643

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871302.pdf?arnumber=9871302

Reference17 articles.

1. Decreased EEG synchronization in Alzheimer's disease and mild cognitive impairment;konig;Neurobiology of Aging,2005

2. Permutation Jaccard Distance-Based Hierarchical Clustering to Estimate EEG Network Density Modifications in MCI Subjects

3. Brain Network Analysis of Compressive Sensed High-Density EEG Signals in AD and MCI Subjects

4. Detection of Early Stage Alzheimer’s Disease using EEG Relative Power with Deep Neural Network

5. A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings

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