Predictive Value of EEG Features for Machine Learning–Based Prediction of Functional Outcome After Thrombectomy in LVO Stroke
- 26 September 2026
- book chapter
- Published by Springer Nature
- p. 15-24
Abstract
No abstract availableKeywords
This publication has 28 references indexed in Scilit:
- Predictors of functional outcome at 3 months in ischemic stroke patients with discharge disability following endovascular therapy: a multi-center observational cohort study of 836 patientsActa Neurochirurgica, 2026
- Review of multimodal machine learning approaches in healthcareInformation Fusion, 2024
- Predicting brain edema and outcomes after thrombectomy in stroke: Frontal delta/alpha ratio as an optimal quantitative EEG indexClinical Neurophysiology, 2024
- Development and Validation of a Postprocedural Model to Predict Outcome After Endovascular Treatment for Ischemic StrokeJAMA Neurology, 2023
- Naïve Bayes Models in Healthcare2023
- Early EEG Alterations Correlate with CTP Hypoperfused Volumes and Neurological Deficit: A Wireless EEG Study in Hyper-Acute Ischemic StrokeAnnals of Biomedical Engineering, 2021
- Hyper-acute EEG alterations predict functional and morphological outcomes in thrombolysis-treated ischemic stroke: a wireless EEG studyMedical & Biological Engineering & Computing, 2020
- The Prognostic Value of Quantitative EEG in Patients Undergoing Mechanical Thrombectomy for Acute Ischemic StrokeJournal Of Clinical Neurophysiology, 2020
- Randomised double-blind placebo-controlled trial of thrombolytic therapy with intravenous alteplase in acute ischaemic stroke (ECASS II)The Lancet, 1998
- The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodogramsIEEE Transactions on Audio and Electroacoustics, 1967