1. Portability rules detection by Epilepsy Tracking META-Set Analysis
- Author
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Christian Riccio, Roberta Siciliano, Michele Staiano, Giuseppe Longo, Luigi Pavone, and Gaetano Zazzaro
- Subjects
Complexity measures ,Data mining ,EEG analysis ,Machine learning ,Meta-analysis ,Seizures detection ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - 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.
- Published
- 2024
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