Portability rules detection by Epilepsy Tracking META-Set Analysis - 20/07/24
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Abstract |
Epilepsy is a severe and common neurological disease that causes sudden and irregular seizures, necessitating patient-specific detection models for effective management. The proposed methodology, Epilepsy Tracking META-Set Analysis, establishes portability rules that identify similar patients, enabling the transfer of these detection models from one patient to another. Main issue is to identify clusters of patients analyzing a set of meta-features of each patient in terms of clinical descriptors, performance metrics of a machine learning model for seizure detection, and data complexity measures. The investigation of complexity measures represents a novelty in such a medical field, allowing to compare patients and to support automated seizure detection methods. The proposed methodology is validated using the well-known Epileptic Seizure EEG Database from the Epilepsy Center of the University Hospital of Freiburg and demonstrates promising results in transferring detection models to new cases.
Le texte complet de cet article est disponible en PDF.Keywords : Complexity measures, Data mining, EEG analysis, Machine learning, Meta-analysis, Seizures detection
Plan
Vol 4 - N° 3
Article 100168- septembre 2024 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.