Exploring The people Cases of Epileptic Patients and Healthy by the CNN Architecture
DOI:
https://doi.org/10.32792/jmed.2025.29.9Keywords:
classification, feature extraction, EEG, deep learning, diagnosis, CNN ArchitectureAbstract
Using electroencephalography (EEG), a unique screening method has beendeveloped to diagnose epileptic episodes. Deep learning is one of the
disciplines of artificial intelligence (DL), which is a broad field. Before the
emergence of deep learning, traditional machine learning methods that
involved feature extraction were used. This restricted their performance to the
skill of the people who crafted the features by hand. On the other hand,
feature extraction and categorization in DL are fully automated. Significant
progress has been made in many fields of medicine since the introduction of
these procedures, including the diagnosis of epileptic seizures. Findings
indicate that the proposed strategy outperforms cutting-edge techniques with
a dataset showing 95.43% accuracy, 0.95% precision, 0.96% recall, and
0.96% F1 score.
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Copyright (c) 2025 Hussein S. Alghannami, Basaad Hadi Hamza, Hadeel K. Aljobouri
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