What question did this study set out to answer?

The aim is to review machine learning and deep learning techniques for detection and prediction of epileptic seizures.

Comprehensive review of machine learning and deep learning techniques for epileptic seizure detection and prediction based on neuroimaging modalities

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Comprehensive review demonstrates machine learning aids detection and prediction of epileptic seizures, suggesting enhanced clinical protocols.

The aim is to review machine learning and deep learning techniques for detection and prediction of epileptic seizures.
Systematic review of computational techniques for seizure detection and prediction
Categorization of machine learning and deep learning algorithms used
Analysis of signal processing methods and neuroimaging modalities
Machine learning and deep learning techniques improve seizure detection accuracy
Highlighting challenges like data scarcity and model generalizability
Identified various neural network architectures enhancing predictive capabilities

Slama et al. (2025) studied this question.

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Comprehensive review demonstrates machine learning aids detection and prediction of epileptic seizures, suggesting enhanced clinical protocols.