Exploring new horizons in neuroscience disease detection through innovative visual signal analysis

NS Amer, SB Belhaouari - Scientific Reports, 2024 - nature.com
Brain disorders pose a substantial global health challenge, persisting as a leading cause of
mortality worldwide. Electroencephalogram (EEG) analysis is crucial for diagnosing brain …

[HTML][HTML] A Novel CNN-Based Framework for Alzheimer's Disease Detection Using EEG Spectrogram Representations

K Stefanou, KD Tzimourta, C Bellos, G Stergios… - Journal of Personalized …, 2025 - mdpi.com
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that
poses critical challenges in global healthcare due to its increasing prevalence and severity …

[PDF][PDF] Leveraging SVD Entropy and Explainable Machine Learning for Alzheimer's and Frontotemporal Dementia Detection using EEG

U Lal, AV Chikkankod, L Longo - Authorea Preprints, 2023 - academia.edu
Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD) represent formidable
neurodegenerative challenges. Existing research into optimal feature-extraction techniques …

A Low Cost CNN-Based Method for Differential Diagnosis of Alzheimer's and Frontotemporal Dementia

BK Jha, MF Siddiqui, A Pandey - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Alzheimer's disease (AD) and Frontotemporal Dementia (FTD) are degenerative
neurological diseases, affecting the cognitive abilities of large elderly populations …

Detecting Cognitive Decline in Alzheimer's Disease using Brain Signals: An EEG Based Classification Approach

AN Mohammed - 2024 IEEE 4th International Maghreb Meeting …, 2024 - ieeexplore.ieee.org
Alzheimer's disease is a long-term illness character-ized by a decline in abilities and the
development of dementia. The main objective of this study is to explore the potential of using …