The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach

Abstract Epilepsy surgery is effective for patients with medication-resistant seizures, however 20–40% of them are not seizure free after surgery. Aim of this study is to evaluate the role of linear and non-linear EEG features to predict post-surgical outcome. We included 123 paediatric patients who...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Mattia Mercier, Chiara Pepi, Giusy Carfi-Pavia, Alessandro De Benedictis, Maria Camilla Rossi Espagnet, Greta Pirani, Federico Vigevano, Carlo Efisio Marras, Nicola Specchio, Luca De Palma
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Nature Portfolio 2024-05-01
Sarja:	Scientific Reports
Aiheet:	Resective surgery Epilepsy Predictive factors Diagnostic evaluation Scalp EEG Brain machine learning
Linkit:	https://doi.org/10.1038/s41598-024-60622-5
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