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Improvement of an automated neonatal seizure detector using a post-processing technique.

, , , , , and . EMBC, page 5859-5862. IEEE, (2015)

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Differences in the cerebral hemodynamics regulation mechanisms of premature infants with intra-ventricular hemorrhage assessed by means of phase rectified signal averaging., , , , , , and . EMBC, page 4208-4211. IEEE, (2014)An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation., , , , , , and . Int. J. Neural Syst., 27 (6): 1750023:1-1750023:18 (2017)Automatic quiet sleep detection based on multifractality in preterm neonates: Effects of maturation., , , , , , , and . EMBC, page 2010-2013. IEEE, (2017)Improved neonatal seizure detection using adaptive learning., , , , , and . EMBC, page 2810-2813. IEEE, (2017)Monitoring of Brain Hemodynamics Coupling in Neonates using Updated Tensor Decompositions., , , , , , , , and . EMBC, page 660-663. IEEE, (2019)Unsupervised Deep Feature Extraction for Neonatal Sleep Stage Classification., , , and . BNAIC/BENELEARN, volume 2491 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels., , , , , , and . IEEE J. Biomed. Health Informatics, 26 (3): 1023-1033 (2022)Preprocessing by means of subspace projections for continuous Cerebral Autoregulation assessment using NIRS., , and . EMBC, page 2032-2035. IEEE, (2013)Neonatal Seizure Detection Using Deep Convolutional Neural Networks., , , , , and . Int. J. Neural Syst., 29 (4): 1850011:1-1850011:20 (2019)Prediction of mental development of preterm newborns at birth time using LS-SVM., , , , , , , , and . ESANN, page 167-172. (2002)