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Portability rules detection by Epilepsy Tracking META-Set Analysis
- Source :
- Neuroscience Informatics, Vol 4, Iss 3, Pp 100168- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
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.
Details
- Language :
- English
- ISSN :
- 27725286
- Volume :
- 4
- Issue :
- 3
- Database :
- Directory of Open Access Journals
- Journal :
- Neuroscience Informatics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.078996a187664e218a4c728579d7107d
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.neuri.2024.100168