Artificial intelligence for brain disease diagnosis using electroencephalogram signals

S Shang, Y Shi, Y Zhang, M Liu, H Zhang… - Journal of Zhejiang …, 2024 - Springer
Brain signals refer to electrical signals or metabolic changes that occur as a consequence of
brain cell activity. Among the various non-invasive measurement methods …

An innovative approach for parkinson's disease diagnosis using CNN, NCA, and SVM

Y Dogan - Neural Computing and Applications, 2024 - Springer
Parkinson's disease (PD) is a prevalent neurodegenerative disorder affecting millions of
people globally, with substantial health risks and economic burdens. This study aims to …

Electroencephalogram (EEG) Based Fuzzy Logic and Spiking Neural Networks (FLSNN) for Advanced Multiple Neurological Disorder Diagnosis

S Jain, R Srivastava - Brain Topography, 2025 - Springer
Neurological disorders are a major global health concern that have a substantial impact on
death rates and quality of life. accurately identifying a number of diseases Due to inherent …

Multiclass classification of epileptic seizure phases using a novel HFO-based feature extraction model

P Sari Tekten, S Kotan, F Kacar - Signal, Image and Video Processing, 2025 - Springer
Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal
neuronal activity in the brain. It can manifest at any age, from childhood to adulthood, with …

Enhancing EEG Signal Classification with a Novel Random Subset Channel Selection Approach: Applications in Taste, Odor, and Motor Imagery Analysis

A Naser, Ö Aydemir - IEEE Access, 2024 - ieeexplore.ieee.org
This study uses various datasets to evaluate the performance of feature extraction and
classification methods for EEG signals. The EEG signals analyzed in this research are …

[ОПИСАНИЕ][C] Unveiling Parkinson's: Handwriting Symptoms with Explainable and Interpretable CNN Model

A Zemmar, A Bennour, M Tahar, F Ghabban… - … Journal of Pattern …, 2025 - World Scientific
Parkinson's disease (PD), the second most prevalent neurodegenerative disorder globally,
afflicting approximately 10 million individuals, necessitates early detection for optimal …