Advancing Alzheimer’s disease detection: a novel convolutional neural network based framework leveraging EEG data and segment length analysis
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Tawhid, Md. Nurul Ahad, Siuly, Siuly 
ORCID: https://orcid.org/0000-0003-2491-0546, Kabir, Enamul ORCID: https://orcid.org/0000-0002-6157-2753 and Li, Yan
(2025)
Advancing Alzheimer’s disease detection: a novel convolutional neural network based framework leveraging EEG data and segment length analysis.
Brain Informatics, 12 (1).
ISSN 2198-4018
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| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/50050 |
| DOI | 10.1186/s40708-025-00260-3 |
| Official URL | https://doi.org/10.1186/s40708-025-00260-3 |
| Subjects | Current > FOR (2020) Classification > 4203 Health services and systems Current > FOR (2020) Classification > 4611 Machine learning Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | alzheimer’s disease (AD); electroencephalogram (EEG); frontotemporal dementia (FTD); CNN; deep learning |
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