Deep Learning Model for Prediction of Dementia Severity based on EEG Signals
This study aimed to determine variations in the electroencephalograms (EEGs) of 15 individuals who were diagnosed with mild cognitive impairment (MCI) following stroke, 5 individuals suffering from vascular dementia (VD) and 15 healthy normal control (NC) individuals who performed a working memory...
Saved in:
| Main Authors: | Noor Kamal Al-Qazzaz, Sawal Hamid Bin Mohd Ali, Siti Anom Ahmad |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Al-Khwarizmi College of Engineering – University of Baghdad
2024-12-01
|
| Series: | Al-Khawarizmi Engineering Journal |
| Online Access: | https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/938 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Role of EEG as Biomarker in the Early Detection and Classification of Dementia
by: Noor Kamal Al-Qazzaz, et al.
Published: (2014-01-01) -
Deep-Learning-Based Mobile Application for Detecting COVID-19
by: Noor Kamal Al-Qazzaz, et al.
Published: (2025-03-01) -
qEEG and Dementia
by: H. Chapman
Published: (2004-09-01) -
An explainable and efficient deep learning framework for EEG-based diagnosis of Alzheimer's disease and frontotemporal dementia
by: Waqar Khan, et al.
Published: (2025-07-01) -
Deep Learning Model for Analyzing EEG Signal Analysis
by: Varun Gupta, et al.
Published: (2025-01-01)