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Characterising Alzheimer’s Disease with EEG-based Energy Landscape Analysis

  • Published:2021 Issue: Volume: Page:1-1
  • ISSN:2168-2194
  • Container-title:IEEE Journal of Biomedical and Health Informatics
  • language:
  • Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Klepl Dominik,He Fei,Wu Min,De Marco Matteo,Blackburn Daniel,Sarrigiannis Ptolemaios Georgios

Funder

Alzheimers Research Trust

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Biotechnology

Cited by 24 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel graph neural network method for Alzheimer’s disease classification;Computers in Biology and Medicine;2024-09

2. PSD-CNN Approach for Subject Independent Dementia Recognition from EEG Signals;2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE);2024-06-19

3. Reliability of energy landscape analysis of resting‐state functional MRI data;European Journal of Neuroscience;2024-06-04

4. Multi Modal EEG-Based Classification of Alzheimer's Disease and Mild Cognitive Impairment Using Hilbert Huang Transform;2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE);2024-05-16

5. Energy landscape analysis of brain network dynamics in Alzheimer’s disease;Frontiers in Aging Neuroscience;2024-05-15
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