What type of study is this?

This is a Literature Review study.

What question did this study set out to answer?

The review identifies challenges in machine learning methods for predicting epileptic seizures using EEG.

May 7, 2026Open Access

Issues and Causal Factors in Machine Learning Methods for Predicting Epileptic Seizures Using EEG: Towards Clinically Viable Prediction via Utility–Latency Feasibility Constraints

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Authors

JDJohn Medina DiazNational University of San Marcos SDSergio Felipe Serrano DiazNational University of San Marcos NCNeeta ChapatwalaASA College

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Implication

Review explores machine learning challenges in seizure prediction, suggesting improvements in efficiency and interpretability for drug-refractory epilepsy.

Key Points

The review identifies challenges in machine learning methods for predicting epileptic seizures using EEG.
Review of existing research on EEG-based seizure prediction
Discussion on dataset design, feature extraction, and classification methods
Proposal of a classification for pipeline and non-pipeline challenges
Highlights issues with current machine learning approaches for seizure prediction
Emphasizes the need for efficiency in algorithms
Suggests frameworks for comparing machine learning methods

Cite This Study

Diaz et al. (2026) studied this question.

synapsesocial.com/papers/69fbe382164b5133a91a2c75 https://doi.org/10.5281/zenodo.20027453

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Implication

Review explores machine learning challenges in seizure prediction, suggesting improvements in efficiency and interpretability for drug-refractory epilepsy.

Issues and Causal Factors in Machine Learning Methods for Predicting Epileptic Seizures Using EEG: Towards Clinically Viable Prediction via Utility–Latency Feasibility Constraints

Discussion

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Implication

Key Points

Cite This Study

Issues and Causal Factors in Machine Learning Methods for Predicting Epileptic Seizures Using EEG: Towards Clinically Viable Prediction via Utility–Latency Feasibility Constraints

Discussion

Member takes

Implication

Key Points

Cite This Study

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