P
Pieter L. Kubben
Researcher at Maastricht University
Publications - 99
Citations - 1949
Pieter L. Kubben is an academic researcher from Maastricht University. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 18, co-authored 85 publications receiving 1189 citations. Previous affiliations of Pieter L. Kubben include Maastricht University Medical Centre & Radboud University Nijmegen.
Papers
More filters
Journal ArticleDOI
Intraoperative MRI-guided resection of glioblastoma multiforme: a systematic review
Pieter L. Kubben,Karlien J Ter Meulen,Olaf E. M. G. Schijns,Mariel ter Laak-Poort,Jacobus J. van Overbeeke,Henk van Santbrink +5 more
TL;DR: Based on the available literature, there is, at best, level 2 evidence that iMRI-guided surgery is more effective than conventional neuronavigation- guided surgery in increasing EOTR, enhancing quality of life, or prolonging survival after resection of glioblastoma multiforme.
Journal ArticleDOI
EEG based multi-class seizure type classification using convolutional neural network and transfer learning
Shivarudhrappa Raghu,Shivarudhrappa Raghu,Natarajan Sriraam,Yasin Temel,Shyam Vasudeva Rao,Pieter L. Kubben +5 more
TL;DR: It can be concluded that the EEG based classification of seizure type using CNN model could be used in pre-surgical evaluation for treating patients with epilepsy.
Journal ArticleDOI
An update on adaptive deep brain stimulation in Parkinson's disease.
Jeroen G. V. Habets,Margot Heijmans,Mark L. Kuijf,Marcus L.F. Janssen,Yasin Temel,Pieter L. Kubben +5 more
TL;DR: This update discusses the most recent developments regarding potential input signals and possible stimulation parameter modulation for adaptive DBS in PD, the feasibility of which can be adapted depending on specific PD phenotypes.
Journal ArticleDOI
Performance evaluation of DWT based sigmoid entropy in time and frequency domains for automated detection of epileptic seizures using SVM classifier.
Shivarudhrappa Raghu,Shivarudhrappa Raghu,Natarajan Sriraam,Yasin Temel,Shyam Vasudeva Rao,Alangar Satyaranjandas Hegde,Pieter L. Kubben +6 more
TL;DR: An automated seizure detection model using a novel computationally efficient feature named sigmoid entropy derived from discrete wavelet transforms that could be used as a potential biomarker for recognition and detection of epileptic seizures is proposed.
Journal ArticleDOI
A novel approach for classification of epileptic seizures using matrix determinant
Shivarudhrappa Raghu,Shivarudhrappa Raghu,Natarajan Sriraam,Alangar Sathyaranjan Hegde,Pieter L. Kubben +4 more
TL;DR: In this article, a matrix determinant of EEG was introduced as a significant feature for recognition of epileptic seizures, and the extracted feature was classified using support vector machine (SVM), K-nearest neighbor (KNN), multi-layer perceptron (MLP) classifiers with 10-fold cross-validation.