S. Huffel

Sabine Van Huffel, Giansalvo Cirrincione, Maurizio Cirrincione, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Generalizations of the total least squares problem

I. Markovsky, S. Huffel, D. Sima, 2010 .

Ambient intelligence in the bedroom

S. Huffel, J. Sloten, T. Willemen, 2015 .

Consistent estimation in the bilinear multivariate errors-in-variables model

I. Markovsky, S. Huffel, A. Kukush, 2003 .

Neuronal activity in the bed nucleus of the stria terminalis in a rat model for obsessive–compulsive disorder

S. Huffel, B. Nuttin, M. Welkenhuysen, 2013, Behavioural Brain Research.

Integrating Diffusion Kurtosis Imaging , Dynamic Susceptibility-Weighted MR imaging and short echo time Chemical Shift Imaging for grading gliomas

S. Huffel, R. Peeters, D. Sima, 2014 .

A fast algorithm for subspace state-space system identification via exploitation of the displacement structure

S. Huffel, P. Dooren, D. Kressner, 2001 .

The generalized total least squares problem: formulation, algorithm and properties

S. Huffel, 1990 .

Detection of epileptic seizures by means of morphological changes in the ECG

Sabine Van Huffel, Lieven Lagae, Carolina Varon, 2013, Computing in Cardiology 2013.

Automated Neonatal Brain Monitoring

S. Huffel, W. Deburchgraeve, M. Vos, 2012 .

On Consistent Estimators in Linear and Bilinear Multivariate Errors-In-Variables Models

I. Markovsky, S. Huffel, A. Kukush, 2002 .

Cuadrados Parciales Using Partial Least Squares for Nonconvulsive Epileptic Seizure Detection

S. Huffel, guez Aldana, F. S. Macías, 2018 .

Extraction of direct respiratory influences form the tachogram using multiscale principal component analysis

Sabine Van Huffel, Devy Widjaja, S. Huffel, 2012 .

Introduction to Total Least Squares and Errors-In-Variables Modeling

Sabine Van Huffel, Philippe Lemmerling, S. Huffel, 2002 .

P152 Detection of nocturnal frontal lobe seizures in pediatric patients by means of accelerometers: preliminary results

Bart Vanrumste, S. Van Huffel, Kris Cuppens, 2009 .

R-DECO: an open-source Matlab based graphical user interface for the detection and correction of R-peaks

Sabine Van Huffel, Jonathan Moeyersons, Carolina Varon, 2019, bioRxiv.

Can Laplacian Eigenmaps Be Used for Differentiation Between Healthy Subjects and Patients With Corrected Tetralogy of Fallot?

Amalia Villa Gómez, S. Huffel, C. Varon, 2020, 2020 Computing in Cardiology.

Fragmented QRS Dynamics Towards Electrical Storm in ICD Patients

S. Huffel, C. Varon, R. Willems, 2020, 2020 Computing in Cardiology.

Activity recognition for physical therapy: fusing signal processing features and movement patterns

Sabine Van Huffel, Lieven Billiet, Thijs Willem Swinnen, 2016, iWOAR.

A Lanczos – like reduction of symmetric structured matrices into semiseparable ones

R. Vandebril, S. Huffel, N. Mastronardi, 2005 .

The use of ultrasound‐based ‘soft markers’ for the prediction of pelvic pathology in women with chronic pelvic pain—can we reduce the need for laparoscopy?

S. Huffel, T. Bourne, D. Timmerman, 2006, BJOG : an international journal of obstetrics and gynaecology.

Quantification of Resonances in Magnetic Resonance Spectra via Principal Component Analysis and Hankel Total Least Squares

S. Huffel, N. Mastronardi, Yu Wang, 1999 .

Logistic Regression and Artificial Neural Networks for Classification of Ovarian Tumors

S. Huffel, D. Timmerman, J. D. Brabanter, 2004 .

A Robust Estimation of the Cardiorespiratory Coupling

John F. Morales, S. Huffel, B. Buyse, 2020 .

Machine Learning to Support Triage of Children at Risk for Epileptic Seizures in the Pediatric Intensive Care Unit

Thomas De Cooman, S. Huffel, D. Eytan, 2022, 2205.05389.

On the equivalence of SVD and TLS based Yule Walker approaches to frequency estimation

T. Söderström, S. Huffel, P. Stoica, 1992 .

Damage in CFRP composite materials monitored with intensity modulated fiber optic sensors

Sabine Van Huffel, Martine Wevers, Laurent Rippert, 2004 .

Reproducibility and variance of short echo time 1H MR chemical shift imaging of the human brain at 3T with automated planning software

Sabine Van Huffel, Jan Luts, Uwe Himmelreich, 2011 .

Estimation in a linear multivariate measurement error model with a change point in the data

Sabine Van Huffel, Alexander Kukush, Ivan Markovsky, 2007, Comput. Stat. Data Anal..

Iteratively reweighted total least squares algorithms for different variances in observations and data

S. Huffel, G. Cirrincione, A. Premoli, 2001 .

Comparison of different compressed sensing algorithms for low SNR 19F application --- imaging of transplanted pancreatic islets with PFCE labeled

Sabine Van Huffel, Sayuan Liang, Karim Louchami, 2015 .

Second order algorithm for imposing independence constraints to the CP model

Sabine Van Huffel, Maarten De Vos, Lieven De Lathauwer, 2008, ISCAS 2008.

Exact and Approximate Modeling of Linear Systems: A Behavioral Approach (Mathematical Modeling and Computation) (Mathematical Modeling and Computation)

Sabine Van Huffel, Bart De Moor, Jan C. Willems, 2006 .

Classification of ovarian tumor using Bayesian least squares support vector machines

Sabine Van Huffel, Johan A. K. Suykens, Dirk Timmerman, 2003 .

Neural signal analysis and artifact removal in single and multichannel in-vivo deep brain recordings

Sabine Van Huffel, Wolfgang Eberle, Carmen Bartic, 2009 .

Biomedical Engineering Systems and Technologies: 5th International Joint Conference, BIOSTEC 2012, Vilamoura, Portugal, February 1-4, 2012, Revised Selected Papers

Sabine Van Huffel, Joaquim Gabriel, Jan Schier, 2013 .

Improved spectral resolution of NMR data by minimum variance signal enhancement

Sabine Van Huffel, Paul Van Hecke, C Decanniere, 1992 .

Comparison of imputation approaches in ovarian tumor diagnostic models based on LS-SVMs

Sabine Van Huffel, Michalis Zervakis, Dirk Timmerman, 2007 .

bioprofile of sleep

Wim Van Paesschen, Sabine Van Huffel, Karen O. Egiazarian, 2005 .

Proceedings of bio-inspired systems and signal processing

Sabine Van Huffel, S. Huffel, 2012, BIOSTEC 2012.

Evaluation of time- and frequency domain methods for the quantification of a multi-component line

Sabine Van Huffel, Paul Van Hecke, D. van Ormondt, 1994 .

Can muscle artifact removal improve seizure detection in scalp EEG

Sabine Van Huffel, Anneleen Vergult, J Gotman, 2006 .

The numerics in control network NICONET

Sabine Van Huffel, A.J.W. van den Boom, S. Huffel, 1998 .

Nonconvulsive epileptic seizure monitoring with incremental learning

Sabine Van Huffel, Borbála Hunyadi, Enrique Juan Marañón Reyes, 2019, Comput. Biol. Medicine.

Using Partial Least Squares for Nonconvulsive Epileptic Seizure Detection

S. Huffel, V. Rodriguez, B. Hunyadi, 2019 .

Temporal Beat-to-Beat Variability of Repolarization Changes Predict Non-Sustained Ventricular Tachycardia in Ischemic Heart Disease Patients

Sabine Van Huffel, Jonathan Moeyersons, Karin Sipido, 2018, 2018 Computing in Cardiology Conference (CinC).

Oxygen Transport to Tissue XXXIII

S. Huffel, M. Rudin, M. Wolf, 2012, Advances in Experimental Medicine and Biology.

How might we combine the information we know about a mass better ? The use of mathematical models to handle medical data

Sabine Van Huffel, Bart De Moor, Dirk Timmerman, 2000 .

Online detection of auditory attention in a neurofeedback application

Sabine Van Huffel, Maarten De Vos, Alexander Bertrand, 2016 .

Tensor- versus matrix-based algorithms in exponential data fitting (abstract)

Sabine Van Huffel, Pierre-Antoine Absil, Mariya Ishteva, 2010 .

The best low multilinear rank approximation of tensors : some practical aspects

L. Lathauwer, S. Huffel, P. Absil, 2010 .

Recent Advances in Biomedical Signal Processing

Sabine Van Huffel, Misha Pavel, Alberto Olivares, 2012 .

Classification with a Deferral Option and Low-Trust Filtering for Automated Seizure Detection

S. Huffel, M. Vos, W. Paesschen, 2020, Sensors.

Departement Elektrotechniek ESAT-SISTA / TR 2003-136 Software for structured total least squares problems : User ’ s guide 1

I. Markovsky, S. Huffel, 2007 .

Motor cortex metabolite alterations in amyotrophic lateral sclerosis assessed in vivo using edited and non-edited magnetic resonance spectroscopy

S. Huffel, R. Peeters, D. Sima, 2019, Brain Research.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization

Sabine Van Huffel, Eric Achten, Frederik Maes, 2017, BMC Medical Imaging.

Hierarchical non-negative matrix factorization using multi-parametric MRI to assess tumor heterogeneity within gliomas

Sabine Van Huffel, Frederik Maes, Jelle Veraart, 2015 .

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation

Sabine Van Huffel, Maarten De Vos, Kirubin Pillay, 2017, Int. J. Neural Syst..

Prevalent breast cancer patients with a homozygous mutant status for CYP2D6*4: response and biomarkers in tamoxifen users

S. Huffel, D. Timmerman, P. Neven, 2009, Breast Cancer Research and Treatment.

Telehealth on heart failure: results of the Recap project

S. Huffel, C. Varon, S. Jaecques, 2015, Journal of telemedicine and telecare.

Early respiratory dysfunction as a biomarker for epileptic encephalopathy

S. Huffel, L. Lagae, K. Jansen, 2013, Acta neurologica Scandinavica.

Bath Ankylosing Spondylitis Functional Index Shows Promising Reliability and Validity in the Assessment of Activity Limitations in Axial Spondyloarthritis

S. Huffel, M. Milosevic, W. Dankaerts, 2016, The Journal of Rheumatology.

Short-term outcome of primary operated early breast cancer by hormone and HER-2 receptors

S. Huffel, P. Neven, V. Belle, 2009, Breast Cancer Research and Treatment.

Bayesian predictive models for ovarian cancer classification : evalution of logistic regression, multi layer perceptron and belief network models in the Bayesian context

Sabine Van Huffel, Joos Vandewalle, Bart De Moor, 2000 .

8. Statistical Properties of the Total Least Squares Problem

Sabine Van Huffel, Joos Vandewalle, J. Vandewalle, 1991 .

The total least squares technique: computation, properties and applications

Sabine Van Huffel, Joos Vandewalle, J. Vandewalle, 1989 .

Structured total least norm and its application to parameter estimation of exponentially damped sinusoids

Sabine Van Huffel, Joos Vandewalle, J. Vandewalle, 1995 .

2. Basic Principles of the Total Least Squares Problem

Sabine Van Huffel, Joos Vandewalle, J. Vandewalle, 1991 .

Decomposition methods in Neuroscience

Sabine Van Huffel, Maarten De Vos, Lieven De Lathauwer, 2010 .

Stress during pregnancy

Marijke A. K. A. Braeken, S. Huffel, J. Taelman, 2010 .

Canonical Decomposition of scalp EEG in epileptic seizure localisation

L. Lathauwer, S. Huffel, M. Vos, 2007, ASILOMAR 2007.

SLICOT subspace identification toolbox

Sabine Van Huffel, Vasile Sima, S. Huffel, 2000 .

Measurement of the liver tissue oxygenation by near-infrared spectroscopy

S. Huffel, G. Naulaers, B. Meyns, 2004, Intensive Care Medicine.

Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image Segmentation

L. Lathauwer, S. Huffel, D. Sima, 2022, Medical Image Anal..

Comparison of BEM and FDM head modeling in SPM for EEG source reconstruction based on free energy

Sabine Van Huffel, Maarten De Vos, Katrien Vanderperren, 2012 .

Concept of bridging the lesion cavity wall with stimulating and recording devices in the central nervous system

Sabine Van Huffel, Jean-Pierre Kruth, Wolfgang Eberle, 2010 .

Reference values of regional cerebral oxygen saturation during the first 3 days of life in preterm neonates

S. Huffel, F. Groenendaal, A. Caicedo, 2016, Pediatric Research.

Removal of Muscle Artifacts from EEG Recordings of Spoken Language Production

Sabine Van Huffel, Maarten De Vos, Stéphanie Riès, 2010, Neuroinformatics.

Patch based super-resolution of MR spectroscopic images

Sabine Van Huffel, Frederik Maes, Dirk Smeets, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Improvement and Validation of an Automated Neonatal Seizure Detector

Sabine Van Huffel, Maarten De Vos, W. Deburchgraeve, 2011, BIOSIGNALS.

Complexity Analysis of Neonatal EEG Using Multiscale Entropy: Applications in Brain Maturation and Sleep Stage Classification

Sabine Van Huffel, Anneleen Dereymaeker, Katrien Jansen, 2017, Entropy.

Decomposition of a Multiscale Entropy Tensor for Sleep Stage Identification in Preterm Infants

Sabine Van Huffel, Gunnar Naulaers, Ofelie De Wel, 2019, Entropy.

Neonatal Seizure Detection Using Deep Convolutional Neural Networks

Sabine Van Huffel, Maarten De Vos, P. J. Cherian, 2019, Int. J. Neural Syst..

Automatic quiet sleep detection based on multifractality in preterm neonates: Effects of maturation

Sabine Van Huffel, Anneleen Dereymaeker, Katrien Jansen, 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Improved multi-stage neonatal seizure detection using a heuristic classifier and a data-driven post-processor

Marina De Vos, P. J. Cherian, S. Van Huffel, 2016, Clinical Neurophysiology.

Evaluation of a Commercial Ballistocardiography Sensor for Sleep Apnea Screening and Sleep Monitoring

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2019, Sensors.

Unsupervised Artefact Detection and Screening Using Emfit Sensor in Patients With Sleep Apnea

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2018, 2018 Computing in Cardiology Conference (CinC).

Improving Reliability of Monitoring Background EEG Dynamics in Asphyxiated Infants

Sabine Van Huffel, Maarten De Vos, Vladimir Matic, 2016, IEEE Transactions on Biomedical Engineering.

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

Sabine Van Huffel, Maarten De Vos, P. J. Cherian, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Removal of BCG artifacts from EEG recordings inside the MR scanner: A comparison of methodological and validation-related aspects

Sabine Van Huffel, Johan Wagemans, Maarten De Vos, 2010, NeuroImage.

Departement Elektrotechniek ESAT-SISTA / TR 2004-51 Application of Structured Total Least Squares for System Identification and Model Reduction 1

Sabine Van Huffel, Bart De Moor, Rik Pintelon, 2007 .

SLICOT—A Subroutine Library in Systems and Control Theory

Sabine Van Huffel, Peter Benner, Andras Varga, 1999 .

Speech compression based on exact modeling and structured total least norm optimization

Sabine Van Huffel, Ioannis Dologlou, Philippe Lemmerling, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

SINGLE-CHANNEL EEG CLASSIFICATION BY MULTI-CHANNEL TENSOR SUBSPACE LEARNING AND REGRESSION

Simon Van Eyndhoven, Sabine Van Huffel, Lieven De Lathauwer, 2018, 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP).

Comparison between Scalp EEG and Behind-the-Ear EEG for Development of a Wearable Seizure Detection System for Patients with Focal Epilepsy

Wim Van Paesschen, Sabine Van Huffel, Borbála Hunyadi, 2017, Sensors.

Two-level ℓ1 minimization for compressed sensing

Sabine Van Huffel, Johan A. K. Suykens, Lei Shi, 2015, Signal Process..

A Geometric Newton Method for Oja's Vector Field

Sabine Van Huffel, Lieven De Lathauwer, Pierre-Antoine Absil, 2008, Neural Computation.

Block term decomposition for modelling epileptic seizures

L. Lathauwer, S. Huffel, M. Vos, 2014, EURASIP J. Adv. Signal Process..

A Combination of Parallel Factor and Independent Component Analysis

Sabine Van Huffel, Maarten De Vos, Lieven De Lathauwer, 2022 .

The “why” and “how” of JointICA: Results from a visual detection task

Sabine Van Huffel, Johan Wagemans, Maarten De Vos, 2012, NeuroImage.

Spatially constrained ICA algorithm with an application in EEG processing

Sabine Van Huffel, Maarten De Vos, Lieven De Lathauwer, 2011, Signal Process..

A generic and extensible automatic classification framework applied to brain tumour diagnosis in HealthAgents

Sabine Van Huffel, Carlos Sáez, Juan Miguel García-Gómez, 2011, The Knowledge Engineering Review.

Removing muscle and eye artifacts using blind source separation techniques in ictal EEG source imaging

M. De Vos, S. Van Huffel, I. Lemahieu, 2009, Clinical Neurophysiology.

Algorithm for imposing SOBI-type constraints on the CP model

Sabine Van Huffel, Maarten De Vos, Lieven De Lathauwer, 2008, 2008 IEEE International Symposium on Circuits and Systems.

Differential-geometric Newton method for the best rank-(R1, R2, R3) approximation of tensors

Sabine Van Huffel, Lieven De Lathauwer, Pierre-Antoine Absil, 2008, Numerical Algorithms.

Structured Total Least Squares

Sabine Van Huffel, Philippe Lemmerling, S. Huffel, 2002 .

Fast Structured Total Least Squares Algorithm for Solving the Basic Deconvolution Problem

Sabine Van Huffel, Nicola Mastronardi, Philippe Lemmerling, 2000, SIAM J. Matrix Anal. Appl..

Solution and properties of the restricted total least squares problem

S. Huffel, 1990 .

10 The total least squares problem

Sabine Van Huffel, Hongyuan Zha, H. Zha, 1993, Computational Statistics.

On the Design of a Web-Based Decision Support System for Brain Tumour Diagnosis Using Distributed Agents

Sabine Van Huffel, Paul H. Lewis, Horacio González-Vélez, 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops.

Automated Detection of Tonic–Clonic Seizures Using 3-D Accelerometry and Surface Electromyography in Pediatric Patients

Sabine Van Huffel, Bart Vanrumste, Bert Bonroy, 2016, IEEE Journal of Biomedical and Health Informatics.

Feature selection methods for accelerometry-based seizure detection in children

Sabine Van Huffel, Bart Vanrumste, Bert Bonroy, 2016, Medical & Biological Engineering & Computing.

Detection of epileptic convulsions from accelerometry signals through machine learning approach

Sabine Van Huffel, Bart Vanrumste, Bert Bonroy, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Accelerometry-Based Home Monitoring for Detection of Nocturnal Hypermotor Seizures Based on Novelty Detection

Sabine Van Huffel, Bart Vanrumste, Peter Karsmakers, 2014, IEEE Journal of Biomedical and Health Informatics.

Detecting rare events using extreme value statistics applied to epileptic convulsions in children

Sabine Van Huffel, Bart Vanrumste, Peter Karsmakers, 2014, Artif. Intell. Medicine.

An approach using extreme value statistics to detect rare movement events in a bio-medical dataset

Sabine Van Huffel, Bart Vanrumste, Peter Karsmakers, 2013 .

Using spatio-temporal interest points (STIP) for myoclonic jerk detection in nocturnal video

Sabine Van Huffel, Bart Vanrumste, Hamid K. Aghajan, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Integrating video and accelerometer signals for nocturnal epileptic seizure detection

Sabine Van Huffel, Bart Vanrumste, Hamid K. Aghajan, 2012, ICMI '12.

Detecting hypermotor seizures using extreme value statistics

Sabine Van Huffel, Bart Vanrumste, Peter Karsmakers, 2012 .

A spline-based tool to assess and visualize the calibration of multiclass risk predictions

Sabine Van Huffel, Dirk Timmerman, Ben Van Calster, 2015, J. Biomed. Informatics.

Support vector methods for survival analysis: a comparison between ranking and regression approaches

Sabine Van Huffel, Vanya Van Belle, Johan A. K. Suykens, 2011, Artif. Intell. Medicine.

Anxious women do not show the expected decrease in cardiovascular stress responsiveness as pregnancy advances

S. Van Huffel, Marijke A. K. A. Braeken, S. Huffel, 2015, Biological Psychology.

Use Case II: Imaging Biomarkers and New Trends for Integrated Glioblastoma Management

Sabine Van Huffel, Juan Miguel García-Gómez, Elena De Angelis, 2017 .

Cardiorespiratory Dynamic Response to Mental Stress: A Multivariate Time-Frequency Analysis

Sabine Van Huffel, Michele Orini, Devy Widjaja, 2013, Comput. Math. Methods Medicine.

The use of ultrasound‐based ‘soft markers’ for the prediction of pelvic pathology in women with chronic pelvic pain—can we reduce the need for laparoscopy?

S. Huffel, T. Bourne, D. Timmerman, 2006, BJOG : an international journal of obstetrics and gynaecology.

Axillary lymph node status of operable breast cancers by combined steroid receptor and HER-2 status: triple positive tumours are more likely lymph node positive

S. Huffel, N. Pochet, D. Timmerman, 2008, Breast Cancer Research and Treatment.

Monitoring of Brain Hemodynamics Coupling in Neonates using Updated Tensor Decompositions

A Caicedo, O De Wel, M Vandecappelle, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

Sabine Van Huffel, Gunnar Naulaers, Alexander Caicedo, 2018, Complex..

Minor component analysis by incremental inverse iteration

Sabine Van Huffel, Diana M. Sima, S. Huffel, 2004 .

The MCA EXIN neuron for the minor component analysis

Sabine Van Huffel, Giansalvo Cirrincione, Maurizio Cirrincione, 2002, IEEE Trans. Neural Networks.

Biomedical Engineering Systems and Technologies

Sabine Van Huffel, Joaquim Gabriel, Jan Schier, 2012, Communications in Computer and Information Science.

Source Separation From Single-Channel Recordings by Combining Empirical-Mode Decomposition and Independent Component Analysis

Sabine Van Huffel, Maarten De Vos, Ivan Gligorijevic, 2010, IEEE Transactions on Biomedical Engineering.

Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram

Wim Van Paesschen, Sabine Van Huffel, Bart Vanrumste, 2006, IEEE Transactions on Biomedical Engineering.

Accelerometry-Based Activity Recognition and Assessment in Rheumatic and Musculoskeletal Diseases

Sabine Van Huffel, Lieven Billiet, Thijs Willem Swinnen, 2016, Sensors.

Tensor decompositions and data fusion in epileptic electroencephalography and functional magnetic resonance imaging data

Patrick Dupont, Wim Van Paesschen, Sabine Van Huffel, 2017, WIREs Data Mining Knowl. Discov..

Learning Transformation Models for Ranking and Survival Analysis

Sabine Van Huffel, Vanya Van Belle, Johan A. K. Suykens, 2011, J. Mach. Learn. Res..

Nosologic Imaging of Brain Tumors Using MRI and MRSI

Sabine Van Huffel, Johan A. K. Suykens, Dirk Vandermeulen, 2011 .

Age interacts with the expression of steroid and HER-2 receptors in operable invasive breast cancer

S. Huffel, D. Timmerman, P. Neven, 2008, Breast Cancer Research and Treatment.

Lobular and non-lobular breast cancers differ regarding axillary lymph node metastasis: a cross-sectional study on 4,292 consecutive patients

S. Huffel, P. Neven, M. Christiaens, 2011, Breast Cancer Research and Treatment.

A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection

Sabine Van Huffel, Johan A. K. Suykens, Jan Luts, 2007, Artif. Intell. Medicine.

Brain tumor classification based on long echo proton MRS signals

Sabine Van Huffel, Johan A. K. Suykens, Carles Arús, 2004, Artif. Intell. Medicine.

Sensorimotor cortex neurometabolite levels as correlate of motor performance in normal aging: evidence from a 1H-MRS study

Sabine Van Huffel, Ronald R. Peeters, Dante Mantini, 2019, NeuroImage.

Data-Driven Clustering of P300 EEG Data Using Coupled Tensor Decompositions

Sabine Van Huffel, S. Huffel, 2017 .

HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis

Sabine Van Huffel, Theodoros N. Arvanitis, Paul H. Lewis, 2009, Applied Intelligence.

On the Implementation of HealthAgents: Agent Based Brain Tumour Diagnosis

Sabine Van Huffel, Paul H. Lewis, Horacio González-Vélez, 2007 .

Agent-Based Distributed Decision Support System for Brain Tumour Diagnosis and Prognosis

Paul H. Lewis, S. Van Huffel, Carles Arús, 2006 .

Effect of feature extraction for brain tumor classification based on short echo time 1H MR spectra

Jan Luts, Montserrat Robles, Arend Heerschap, 2008, Magnetic resonance in medicine.

Best Low Multilinear Rank Approximation of Higher-Order Tensors, Based on the Riemannian Trust-Region Scheme

Sabine Van Huffel, Lieven De Lathauwer, Pierre-Antoine Absil, 2011, SIAM J. Matrix Anal. Appl..

Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints

Sabine Van Huffel, Vanya Van Belle, Johan A. K. Suykens, 2009, IWANN.

Perceptual audio modeling with exponentially damped sinusoids

Sabine Van Huffel, Patrick Wambacq, Werner Verhelst, 2005, Signal Process..

Single Trial Classification for Mobile BCI - A Multiway Kernel Approach

Sabine Van Huffel, Michel Verleysen, Maarten De Vos, 2015, BIOSIGNALS.

Exact and Approximate Modeling of Linear Systems: A Behavioral Approach

S. Van Huffel, Jan C. Willems, B. De Moor, 2006 .

The dynamics of contour integration: A simultaneous EEG–fMRI study

Sabine Van Huffel, Johan Wagemans, Maarten De Vos, 2014, NeuroImage.

Effect of telehealth on self-care behavior of heart failure patients

Sabine Van Huffel, Carolina Varon, Stuart Thomson, 2014, Computing in Cardiology 2014.

Interval Coded Scoring: a toolbox for interpretable scoring systems

Sabine Van Huffel, Vanya Van Belle, Lieven Billiet, 2018, PeerJ Comput. Sci..

Risk group detection and survival function estimation for interval coded survival methods

Stephen P. Boyd, J. Suykens, S. Huffel, 2013, Neurocomputing.

Capacitively-Coupled ECG and Respiration for Sleep–Wake Prediction and Risk Detection in Sleep Apnea Patients

S. Huffel, T. Torfs, B. Buyse, 2021, Sensors.

Sleep Diagnostics for Home Monitoring of Sleep Apnea Patients

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2021, Frontiers in Digital Health.

A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2015, IEEE Transactions on Biomedical Engineering.

Improved performance on high-dimensional survival data by application of Survival-SVM

Sabine Van Huffel, Vanya Van Belle, Johan A. K. Suykens, 2011, Bioinform..

MINLIP: Efficient Learning of Transformation Models

Sabine Van Huffel, Vanya Van Belle, Johan A. K. Suykens, 2009, ICANN.

Irregular heartbeat detection using sequentially truncated multilinear singular value decomposition

Sabine Van Huffel, Carlos R. Vázquez-Seisdedos, Alexander A. Suárez León, 2017, 2017 Computing in Cardiology (CinC).

Irregular heartbeats detection using tensors and Support Vector Machines

Sabine Van Huffel, Carlos R. Vázquez-Seisdedos, Alexander A. Suárez León, 2016, 2016 Computing in Cardiology Conference (CinC).

Characterization of the respiratory and heart beat signal from an air pressure-based ballistocardiographic setup

Sabine Van Huffel, Jos Vander Sloten, Bart Haex, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Stress classification by separation of respiratory modulations in heart rate variability using orthogonal subspace projection

Sabine Van Huffel, Devy Widjaja, Elke Vlemincx, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Cardiac autonomic dysfunction in West syndrome

S. Huffel, L. Lagae, S. Vandeput, 2012, Epilepsy Research.

Phase-rectified Signal Averaging for the Quantification of the Influence of Prenatal Anxiety on Heart Rate Variability of Babies

Sabine Van Huffel, Katrien Vanderperren, Renée A. Otte, 2012, BIOSIGNALS.

Pulse photoplethysmography derived respiration for obstructive sleep apnea detection

Sabine Van Huffel, Jesús Lázaro, Eduardo Gil, 2017, 2017 Computing in Cardiology (CinC).

Antenatal Maternal Anxiety is Related to HPA-Axis Dysregulation and Self-Reported Depressive Symptoms in Adolescence: A Prospective Study on the Fetal Origins of Depressed Mood

S. Huffel, L. Lagae, B. Calster, 2008, Neuropsychopharmacology.

Online Automated Seizure Detection in Temporal Lobe Epilepsy Patients Using Single-lead ECG

Wim Van Paesschen, Sabine Van Huffel, Borbála Hunyadi, 2017, Int. J. Neural Syst..

Fast algorithms for structured total least squares in speech compression

Sabine Van Huffel, Nicola Mastronardi, Philippe Lemmerling, 2001 .

Fast structured total least squares algorithms via exploitation of the displacement structure

Sabine Van Huffel, Nicola Mastronardi, Philippe Lemmerling, 2002 .

Ictal and interictal respiratory changes in temporal lobe and absence epilepsy in childhood

Sabine Van Huffel, Lieven Lagae, Carolina Varon, 2013, Epilepsy Research.

Does a normal scan exclude the presence of significant pathology in women with chronic pelvic pain

S. Huffel, T. Bourne, D. Timmerman, 2003 .

Unsupervised tissue segmentation of MRSI data using Canonical Correlation Analysis

Sabine Van Huffel, Paul Van Hecke, Lieven De Lathauwer, 2005 .

A Lanczos–like reduction of symmetric structured matrices to semiseparable form*

S. Van Huffel, Raf Vandebril, Nicola Mastronardi, 2005 .

Best multilinear rank approximation of tensors : a trust-region algorithm and local mimina (Best poster award)

Sabine Van Huffel, Lieven De Lathauwer, Pierre-Antoine Absil, 2009 .

Canonical decomposition of ictal scalp EEG reliably detects the seizure onset zone

Patrick Dupont, M. De Vos, S. Van Huffel, 2007, NeuroImage.

Metabolite Quantification in MRS and Pattern Recognition

Sabine Van Huffel, Diana Sima, Jean-Baptiste Poullet, 2009 .

An efficient and reliable algorithm for computing the singular subspace of a matrix, associated with its smallest singular values

Sabine Van Huffel, Joos Vandewalle, J. Vandewalle, 1987 .

Fast algorithm for solving the Hankel/Toeplitz Structured Total Least Squares problem

Sabine Van Huffel, Nicola Mastronardi, Philippe Lemmerling, 2004, Numerical Algorithms.

Multi-structural Signal Recovery for Biomedical Compressive Sensing

Sabine Van Huffel, Maarten De Vos, Yuqian Li, 2013, IEEE Transactions on Biomedical Engineering.

Benchmarking Transfer Entropy Methods for the Study of Linear and Nonlinear Cardio-Respiratory Interactions

Sabine Van Huffel, Jonathan Moeyersons, Enrico G. Caiani, 2021, Entropy.

Overview of total least-squares methods

Sabine Van Huffel, Ivan Markovsky, I. Markovsky, 2007, Signal Process..

Total Least Squares and Errors-in-variables Modeling

Sabine Van Huffel, Alexander Kukush, Nicola Mastronardi, 2007, Comput. Stat. Data Anal..

Total Least Squares and Errors- In-Variables Modeling: Bridging the Gap Between Statistics, Computational Mathematics and Engineering

Sabine Van Huffel, S. Huffel, 2002 .

Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data

Simon Van Eyndhoven, S. Huffel, P. Dupont, 2020, NeuroImage.

Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption — A β-Divergence Approach

Sergios Theodoridis, Michiel Vandecappelle, Lieven De Lathauwer, 2019, 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Canonical Decomposition of Ictal Scalp EEG and Accurate Source Localisation: Principles and Simulation Study

Wim Van Paesschen, Sabine Van Huffel, Maarten De Vos, 2007, Comput. Intell. Neurosci..

Imposing Independence Constraints in the CP Model

Sabine Van Huffel, Maarten De Vos, Lieven De Lathauwer, 2007, ICA.

ResearchArticle Canonical Decomposition of Ictal Scalp EEG and Accurate Source Localisation: Principles and Simulation Study

Sabine Van Huffel, Maarten De Vos, Bart Vanrumste, 2007 .

Exponential data fitting using multilinear algebra: the single‐channel and multi‐channel case

Sabine Van Huffel, Lieven De Lathauwer, Jean-Michel Papy, 2005, Numer. Linear Algebra Appl..

Exponential Data Fitting and Its Applications

Sabine Van Huffel, Kaustav Banerjee, Dianne P. O'Leary, 2018 .

Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation

Sabine Van Huffel, Chris Van Hoof, Willemijn Groenendaal, 2020, Sensors.

Subspace-based exponential data modeling using prior knowledge

Sabine Van Huffel, D. van Ormondt, S. Huffel, 1998 .

Using prior knowledge in SVD-based parameter estimation for magnetic resonance spectroscopy-the ATP example

Sabine Van Huffel, Petre Stoica, Yngve Selén, 2004, IEEE Transactions on Biomedical Engineering.

Using prior knowledge in SVD-based NMR spectroscopy - the ATP example

Sabine Van Huffel, Petre Stoica, Yngve Selén, 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

Time-domain spectroscopic quantitation

Sabine Van Huffel, Paul Van Hecke, Leentje Vanhamme, 2002 .

Biomedical Magnetic Resonance Spectroscopic Quantitation : a Review of Modern time-domain Analysis Methods

S. Van Huffel, Leentje Vanhamme, P. Van Hecke, 2001 .

Formulation and solution of structured total least norm problems for parameter estimation

Sabine Van Huffel, J. Ben Rosen, Haesun Park, 1996, IEEE Trans. Signal Process..

Artefact Detection in Impedance Pneumography Signals: A Machine Learning Approach

Sabine Van Huffel, Chris Van Hoof, Jonathan Moeyersons, 2021, Sensors.

A prospective fMRI-based technique for localising the epileptogenic zone in presurgical evaluation of epilepsy

Patrick Dupont, Simon Tousseyn, Wim Van Paesschen, 2015, NeuroImage.

Incorporating structural information from the multichannel EEG improves patient-specific seizure detection

Wim Van Paesschen, Johan A. K. Suykens, Maarten De Vos, 2012, Clinical Neurophysiology.

Statistical analysis of neural spike trains for evaluation of functional differences in brain activity

Sabine Van Huffel, Wolfgang Eberle, Carmen Bartic, 2010 .

Reliability of Statistical Features Describing Neural Spike Trains in the Presence of Classification Errors

Sabine Van Huffel, Ivan Gligorijevic, Ninah Koolen, 2012, BIOSIGNALS.

Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome

S. Huffel, S. Van Huffel, D. Sappey-Marinier, 2022, Frontiers in Robotics and AI.

Recent advances in total least squares techniques and errors-in-variables modeling

Sabine Van Huffel, Errors-in-Variables Modeling, S. Huffel, 1997 .

TLS based methods for exponential parameter estimation

S. Huffel, E. Dowling, R. DeGroat, 1997 .

TLS applications in biomedical signal processing

Sabine Van Huffel, S. Huffel, 1997 .

Fast algorithms for signal subspace fitting with toeplitz matrices and applications to exponential data modeling

S. Van Huffel, Philippe Lemmerling, Leentje Vanhamme, 1995 .

The partial total least squares algorithm

Sabine Van Huffel, Joos Vandewalle, J. Vandewalle, 1988 .

Quantification of prostate MRSI data by model‐based time domain fitting and frequency domain analysis

John Kurhanewicz, Leentje Vanhamme, Pieter Pels, 2006, NMR in biomedicine.

New approaches for the adaptive segmentation of neonatal EEG signals

Sabine Van Huffel, Maarten De Vos, W. Deburchgraeve, 2009 .

The use of total least squares data fitting in the shape-from-moments problem

Sabine Van Huffel, Lieven De Lathauwer, Philippe Lemmerling, 2006, Signal Process..

Common pole estimation in multi-channel exponential data modeling

Sabine Van Huffel, Lieven De Lathauwer, Jean-Michel Papy, 2006, Signal Process..

Antenatal Maternal Anxiety is Related to HPA-Axis Dysregulation and Self-Reported Depressive Symptoms in Adolescence: A Prospective Study on the Fetal Origins of Depressed Mood

S. Huffel, L. Lagae, B. Calster, 2008, Neuropsychopharmacology.

NMR spectroscopy quantitation

P V Hecke, S. Huffel, S V Huffel, 2001, NMR in biomedicine.

Analysis of the Structured Total Least Squares Problem for Hankel/Toeplitz Matrices

Sabine Van Huffel, Philippe Lemmerling, S. Huffel, 2004, Numerical Algorithms.

Effect of the static magnetic field of the MR-scanner on ERPs: Evaluation of visual, cognitive and motor potentials

I. Lemahieu, S. Assecondi, K. Vanderperren, 2010, Clinical Neurophysiology.

Assessment of different methodologies to include temporal information in classifying episodes of sleep apnea based on single-lead electrocardiogram

Sabine Van Huffel, Jos Vander Sloten, Bart Haex, 2014, Computing in Cardiology 2014.

An Evaluation of Cardiorespiratory and Movement Features With Respect to Sleep-Stage Classification

Sabine Van Huffel, Vasileios Exadaktylos, Jos Vander Sloten, 2014, IEEE Journal of Biomedical and Health Informatics.

Asymptotic hypothesis test to compare likelihood ratios of multiple diagnostic tests in unpaired des

S. Huffel, J. Luts, J. A. R. Nofuentes, 2011 .

Fast and stable two‐way algorithm for diagonal plus semi‐separable systems of linear equations

Sabine Van Huffel, Shivkumar Chandrasekaran, Nicola Mastronardi, 2001 .

Validation of a new automated neonatal seizure detection system: A clinician’s perspective

M. De Vos, W. Deburchgraeve, R. M. Swarte, 2011, Clinical Neurophysiology.

Feature Selection Algorithm based on Random Forest applied to Sleep Apnea Detection

Dries Testelmans, Bertien Buyse, Margot Deviaene, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy

Sabine Van Huffel, Paulo J. G. Lisboa, Dirk Timmerman, 2007, ISNN.

Mapping Approximation by the GMR Neural Network

Sabine Van Huffel, Maurizio Cirrincione, G. Cirrincione, 2000 .

Multi-class AUC metrics and weighted alternatives

Sabine Van Huffel, Vanya Van Belle, Dirk Timmerman, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

The Power of Tensor-Based Approaches in Cardiac Applications

Sabine Van Huffel, Sibasankar Padhy, Lieven De Lathauwer, 2019, Series in BioEngineering.

Irregular heartbeat classification using Kronecker Product Equations

Nico Vervliet, Sabine Van Huffel, Lieven De Lathauwer, 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Fast algorithms for exponential data modeling

Sabine Van Huffel, Haesun Park, Lars Eldén, 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

Compressed Sensing of Multichannel EEG Signals: The Simultaneous Cosparsity and Low-Rank Optimization

Sabine Van Huffel, Maarten De Vos, Yipeng Liu, 2015, IEEE Transactions on Biomedical Engineering.

Prospective study of uterine sonographic changes after 3 months endocrine treatment in postmenopausal breast cancer patients: tamoxifen is estrogenic while aromatase inhibitors induce atrophy and can reverse the effect of tamoxifen

S. Huffel, D. Timmerman, P. Neven, 2003 .

The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals

Sabine Van Huffel, Johan A. K. Suykens, Carles Arús, 2002, The European Symposium on Artificial Neural Networks.

Menopausal symptoms and uterine changes in postmenopausal breast cancer patients receiving tamoxifen or third generation aromatase inhibitors

S. Huffel, D. Timmerman, P. Neven, 2004 .

Prospective study on the effect of endocrine treatments on menopausal symptoms in breast cancer patients

S. Huffel, D. Timmerman, P. Neven, 2003 .

Mobile EEG on the bike: disentangling attentional and physical contributions to auditory attention tasks

Sabine Van Huffel, Maarten De Vos, Borbála Hunyadi, 2016, Journal of neural engineering.

Early soft and flexible fusion of EEG and fMRI via tensor decompositions pdf

Sabine Van Huffel, Lieven De Lathauwer, Sergios Theodoridis, 2020, ArXiv.

Automatic video detection of body movement during sleep based on optical flow in pediatric patients with epilepsy

Sabine Van Huffel, Bart Vanrumste, Kris Cuppens, 2010, Medical & Biological Engineering & Computing.

Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase.

Sabine Van Huffel, Maarten De Vos, Borbála Hunyadi, 2016, Journal of neural engineering.

Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment

Wim Van Paesschen, Sabine Van Huffel, Borbála Hunyadi, 2017, Sensors.

Estimation of the maximal heart rate to improve online tonic-clonic seizure detection using ECG

Wim Van Paesschen, Sabine Van Huffel, Bart Vanrumste, 2015, 2015 Computing in Cardiology Conference (CinC).

Online seizure detection in adults with temporal lobe epilepsy using single-lead ECG

Sabine Van Huffel, Evelien Carrette, Alfred Meurs, 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

Heart beat detection in multimodal data using signal recognition and beat location estimation

Sabine Van Huffel, Carolina Varon, Griet Goovaerts, 2014, Computing in Cardiology 2014.

Results of quantitative EEG analysis are associated with autism spectrum disorder and development abnormalities in infants with tuberous sclerosis complex

Sabine Van Huffel, Pavel Krsek, Konrad Wojdan, 2021, Biomed. Signal Process. Control..

Monitoring Effective Connectivity in the Preterm Brain: A Graph Approach to Study Maturation

Sabine Van Huffel, Anneleen Dereymaeker, Katrien Jansen, 2017, Complex..

A new and fast approach towards sEMG decomposition

S. Huffel, J. Blok, M. Vos, 2013, Medical & Biological Engineering & Computing.

Identifying Stable Components of Matrix /Tensor Factorizations via Low-Rank Approximation of Inter-Factorization Similarity

Simon Van Eyndhoven, Nico Vervliet, Sabine Van Huffel, 2019, 2019 27th European Signal Processing Conference (EUSIPCO).

Detection of irregular heartbeats using tensors

Sabine Van Huffel, Rik Willems, Griet Goovaerts, 2015, 2015 Computing in Cardiology Conference (CinC).

Bayesian model selection of template forward models for EEG source reconstruction

Sabine Van Huffel, Maarten De Vos, Hans Hallez, 2014, NeuroImage.

Time-frequency heart rate variability characteristics of young adults during physical, mental and combined stress in laboratory environment

Sabine Van Huffel, Arthur Spaepen, Ivan Gligorijevic, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

FAST report: short-echo time MRS quantitation

Sabine Van Huffel, Diana Sima, Jean-Baptiste Poullet, 2008 .

Automation of spectroscopic scoring of prostate MRSI by a canonical analysis based classification

Sabine Van Huffel, Maarten De Vos, John Kurhanewicz, 2006 .

Advanced time-domain quantitation methods for MR spectroscopy and metabolite imaging

S. Van Huffel, D. van Ormondt, R. de Beer, 1996 .

Fast and accurate parameter estimation of noisy complex exponentials with use of prior knowledge

Sabine Van Huffel, Leentje Vanhamme, Aad van den Boogaart, 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

Application of the structured total least norm technique in spectral estimation

Sabine Van Huffel, Dirk van Ormondt, Hua Chen, 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

IMPROVED QUANTITATIVE TIME-DOMAIN ANALYSIS OF NMR DATA BY TOTAL LEAST SQUARES.

S. Van Huffel, Joos Vandewalle, C Decanniere, 1991 .

Modeling common dynamics in multichannel signals with applications to artifact and background removal in EEG recordings

Wim Van Paesschen, Sabine Van Huffel, Bart Vanrumste, 2005, IEEE Transactions on Biomedical Engineering.

Consistent least squares fitting of ellipsoids

Sabine Van Huffel, Alexander Kukush, Ivan Markovsky, 2004, Numerische Mathematik.

Automated T Wave End Detection Methods - Comparison of Four Different Methods for T Wave End Detection

Sabine Van Huffel, Jonathan Moeyersons, Rik Willems, 2017, BIOSIGNALS.

Independent component analysis as a preprocessing step for data compression of neonatal EEG

Sabine Van Huffel, Maarten De Vos, Vladimir Matic, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Oxygen Transport to Tissue XXXV

Sabine Van Huffel, Gunnar Naulaers, David K. Harrison, 2013, Advances in Experimental Medicine and Biology.

phenotype in fathers, but not in mothers and siblings Quantitative autism traits in first degree relatives: evidence for the broader autism

S. Huffel, J. Luts, I. Noens, 2012 .

The Progression of Heart Rate Variability Parameters Throughout Cardiac Rehabilitation

John F. Morales, S. Huffel, P. Vandervoort, 2019, 2019 Computing in Cardiology (CinC).

Sleep Apnea Hypopnea Syndrome classification in SpO2 signals using wavelet decomposition and phase space reconstruction

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2017, 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

Spectral subtraction method applied to damage detection in composite materials with embedded optical fibers

Sabine Van Huffel, Martine Wevers, Laurent Rippert, 2001 .

A Semi-Automated Segmentation Framework for MRI Based Brain Tumor Segmentation Using Regularized Nonnegative Matrix Factorization

Sabine Van Huffel, Eric Achten, Frederik Maes, 2016, 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS).

Level choice in truncated total least squares

Sabine Van Huffel, Diana Maria Sima, S. Huffel, 2007, Comput. Stat. Data Anal..

The element-wise weighted total least-squares problem

Sabine Van Huffel, Alexander Kukush, Maria Luisa Rastello, 2006, Comput. Stat. Data Anal..

The use of a new logistic regression model for predicting the outcome of pregnancies of unknown location

S. Van Huffel, George Condous, Tom Bourne, 2004 .

On the equivalence between total least squares and maximum likelihood PCA

S. Van Huffel, Peter D. Wentzell, Ivan Markovsky, 2005 .

On the accuracy of total least squares and least squares techniques in the presence of errors on all data

Sabine Van Huffel, Joos Vandewalle, J. Vandewalle, 1989, Autom..

NMF in MR Spectroscopy

S. Van Huffel, Nicolas Sauwen, Diana Sima, 2016 .

Combining HR-MAS and In Vivo MRI and MRSI Information for Robust Brain Tumor Recognition

S. Van Huffel, M. C. Martínez-Bisbal, T. Laudadio, 2009 .

An advanced MRI and MRSI data fusion scheme for enhancing unsupervised brain tumor differentiation

Sabine Van Huffel, Xin Liu, Yi Yao, 2017, Comput. Biol. Medicine.

Unsupervised Nosologic Imaging for Glioma Diagnosis

Sabine Van Huffel, Yiming Pi, Yuqian Li, 2013, IEEE Transactions on Biomedical Engineering.

On the relevance of automatically selected single-voxel MRS and multimodal MRI and MRSI features for brain tumour differentiation

Sabine Van Huffel, Johan A. K. Suykens, Jan Luts, 2011, Comput. Biol. Medicine.

Differentation between brain metastasis and glioblastoma using MRI and two-dimensional Turbo spectroscopic imaging data

Jan Luts, Bernardo Celda, Sabine Van Huffel, 2009 .

Validity in the Assessment of Activity Limitations in Axial Spondyloarthritis Bath Ankylosing Spondylitis Functional Index Shows Promising Reliability and Westhovens and

S. Huffel, M. Milosevic, W. Dankaerts, 2016 .

Self-reported symptoms of depressed mood, trait anxiety and aggressive behavior in post-pubertal adolescents: Associations with diurnal cortisol profiles

S. Huffel, B. Calster, B. V. D. Bergh, 2008, Hormones and Behavior.

Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI

Sabine Van Huffel, Johan A. K. Suykens, Jan Luts, 2009, 2009 22nd IEEE International Symposium on Computer-Based Medical Systems.

On the conic section fitting problem

Sabine Van Huffel, Alexander Kukush, Sergiy Shklyar, 2007 .

Consistent estimation in an implicit quadratic measurement error model

Sabine Van Huffel, Alexander Kukush, Ivan Markovsky, 2004, Comput. Stat. Data Anal..

The BOLD correlates of the visual P1 and N1 in single-trial analysis of simultaneous EEG-fMRI recordings during a spatial detection task

Sabine Van Huffel, Johan Wagemans, Maarten De Vos, 2011, NeuroImage.

An application of methods for the probabilistic three-class classification of pregnancies of unknown location

Sabine Van Huffel, Dirk Timmerman, Ben Van Calster, 2009, Artif. Intell. Medicine.

Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression

Sabine Van Huffel, Johan A. K. Suykens, Dirk Timmerman, 2007, ICANN.

Evaluation of methods for determining a pre-ictal state in scalp-EEG measurements

Wim Van Paesschen, Sabine Van Huffel, Wim De Clercq, 2002 .

Special issue on linear algebra in signal and image processing - Preface

Sabine Van Huffel, Per Christian Hansen, P Maass, 2004 .

SLICOT, a subroutine library in control and systems theory

Sven Hammarling, F. Dumortier, A.J.W. van den Boom, 1991 .

2. Approximate Modeling via Misfit Minimization

Sabine Van Huffel, Bart De Moor, Jan C. Willems, 2006 .

Continuous measurement of cerebral blood volume and oxygenation during rewarming of neonates

S. Huffel, G. Morren, G. Naulaers, 2004, Acta paediatrica.

Time-Domain Methods for Quantifying MR Spectra

Sabine Van Huffel, Dirk van Ormondt, Diana M. Sima, 2015 .

Cerebral Tissue Oxygenation and Regional Oxygen Saturation Can Be Used to Study Cerebral Autoregulation in Prematurely Born Infants

Sabine Van Huffel, Gunnar Naulaers, Alexander Caicedo, 2011, Pediatric Research.

Bayesian networks in ovarian cancer diagnosis: potentials and limitations

Sabine Van Huffel, Bart De Moor, Dirk Timmerman, 2000, Proceedings 13th IEEE Symposium on Computer-Based Medical Systems. CBMS 2000.

Predicting Left Ventricular Mass Using ECG, Demographic and DXA Features

S. Huffel, J. Bogaert, C. Varon, 2020, 2020 Computing in Cardiology.

Automatic Video Detection of Nocturnal Epileptic Movement based on Motion Tracks

Sabine Van Huffel, Bart Vanrumste, Tinne Tuytelaars, 2012, BIOSIGNALS.

11. Approximate System Identification

Sabine Van Huffel, Bart De Moor, Jan C. Willems, 2006 .

The Total Least Squares Problem in AX ≈ B: A New Classification with the Relationship to the Classical Works

Sabine Van Huffel, Zdenek Strakos, Diana Maria Sima, 2011, SIAM J. Matrix Anal. Appl..

Improved quantification of MRSI data using spatial constraints

Sabine Van Huffel, Anca Croitor Sava, Diana Sima, 2009 .

Application of Kernel Principal Component Analysis for Single-Lead-ECG-Derived Respiration

Sabine Van Huffel, Johan A. K. Suykens, Carolina Varon, 2012, IEEE Transactions on Biomedical Engineering.

Comparison and combination of electrocardiogram, electromyogram and accelerometry for tonic-clonic seizure detection in children

Sabine Van Huffel, Lieven Lagae, Berten Ceulemans, 2018, 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

Flexible fusion of electroencephalography and functional magnetic resonance imaging: Revealing neural-hemodynamic coupling through structured matrix-tensor factorization

Simon Van Eyndhoven, Sabine Van Huffel, Lieven De Lathauwer, 2017, 2017 25th European Signal Processing Conference (EUSIPCO).

Fusion of electroencephalography and functional magnetic resonance imaging to explore epileptic network activity

Wim Van Paesschen, Sabine Van Huffel, Maarten De Vos, 2016, 2016 24th European Signal Processing Conference (EUSIPCO).

Exploring the epileptic network with parallel ICA of interictal EEG-FMRI

Wim Van Paesschen, Sabine Van Huffel, Maarten De Vos, 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

Incorporating higher dimensionality in joint decomposition of EEG and fMRI

Sabine Van Huffel, Maarten De Vos, Borbála Hunyadi, 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

Automated way to obtain motor units' signatures and estimate their firing patterns during voluntary contractions using HD-sEMG

Sabine Van Huffel, Maarten De Vos, Ivan Gligorijevic, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

MAGNETIC RESONANCE SPECTROSCOPY DATA QUANTIFICATION

S. Huffel, P. Lemmerling, P. Hecke, 2004 .

Improved Fitting Method for Parameter Estimation of MRS Signals with Prior Knowledge

Sabine Van Huffel, Leentje Vanhamme, A. van den Boogaart, 1997 .

A perinatal stress calculator for the neonatal intensive care unit: an unobtrusive approach

S. Huffel, S. Van Huffel, E. Ortibus, 2020, Physiological measurement.

Additive survival least‐squares support vector machines

S Van Huffel, V Van Belle, K Pelckmans, 2010, Statistics in medicine.

On the equivalence of constrained total least squares and structured total least squares

Sabine Van Huffel, Bart De Moor, Philippe Lemmerling, 1996, IEEE Trans. Signal Process..

Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines

Sabine Van Huffel, Johan A. K. Suykens, Dirk Timmerman, 2003, Artif. Intell. Medicine.

Sleep Apnea Detection Using Pulse Photoplethysmography

Sabine Van Huffel, Jesús Lázaro, Carolina Varon, 2018, 2018 Computing in Cardiology Conference (CinC).

Assessing cardiovascular comorbidities in sleep apnea patients using SpO2

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2017, 2017 Computing in Cardiology (CinC).

Comparison of the performance of matrix and tensor based multi-channel harmonic analysis

L. Lathauwer, S. Huffel, Mariya Ishteva, 2006 .

Quantification of the glycogen 13C‐1 NMR signal during glycogen synthesis in perfused rat liver

S. Huffel, S. Van Huffel, T. Dresselaers, 2003, NMR in biomedicine.

Prenatal anxiety flattening of the day-time cortisol profile and depression in adolesence

S. Huffel, L. Lagae, B. Calster, 2006 .

Early development of synchrony in cortical activations in the human

Marina De Vos, S. Van Huffel, A. Dereymaeker, 2016, Neuroscience.

Bandpass prefiltering for exponential data fitting with known frequency region of interest

Sabine Van Huffel, Joos Vandewalle, Hua Chen, 1996, Signal Process..

Improved method for accurate and efficient quantification of MRS data with use of prior knowledge

Vanhamme, van den Boogaart A, Van Huffel S, 1997, Journal of magnetic resonance.

Interval Coded Scoring extensions for larger problems

Sabine Van Huffel, Vanya Van Belle, Lieven Billiet, 2017, 2017 IEEE Symposium on Computers and Communications (ISCC).

Interval Coded Scoring Index with Interaction Effects - A Sensitivity Study

Sabine Van Huffel, Vanya Van Belle, Lieven Billiet, 2016, ICPRAM.

Binary Reweighted l1-Norm Minimization for One-Bit Compressed Sensing

Sabine Van Huffel, Hui Wang, Qun Wan, 2015, BIOSIGNALS.

Robust Sparse Signal Recovery for Compressed Sensing with Sampling and Dictionary Uncertainties pdf

Sabine Van Huffel, Yipeng Liu, Maarten De Vos, 2013, ArXiv.

Automated artifact removal as preprocessing refines neonatal seizure detection

M. De Vos, W. Deburchgraeve, P. J. Cherian, 2011, Clinical Neurophysiology.

Comparison of ICA algorithms for ECG artifact removal from EEG signals

Sabine Van Huffel, W. Deburchgraeve, Vladimir Matic, 2009 .

Artefact detection and quality assessment of ambulatory ECG signals

Sabine Van Huffel, Jonathan Moeyersons, Elena Smets, 2019, Comput. Methods Programs Biomed..

Robust artefact detection in long-term ECG recordings based on autocorrelation function similarity and percentile analysis

Sabine Van Huffel, Johan A. K. Suykens, Carolina Varon, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Quantification of magnetic resonance spectroscopy signals with lineshape estimation

S. Van Huffel, U. Himmelreich, S. Huffel, 2011 .

Probabilistic cardiac and respiratory based classification of sleep and apneic events in subjects with sleep apnea

S. Huffel, S. Van Huffel, J. Sloten, 2015, Physiological measurement.

Multiple sparse volumetric priors for distributed EEG source reconstruction

Sabine Van Huffel, Maarten De Vos, Hans Hallez, 2014, NeuroImage.

Advanced EEG Processing for the Detection of Drowsiness in Drivers

Sabine Van Huffel, Milica Milosevic, Griet Goovaerts, 2014, BIOSIGNALS.

Support vector machines for survival analysis

Sabine Van Huffel, Vanya Van Belle, Johan A. K. Suykens, 2007 .

Survival SVM: a practical scalable algorithm

Sabine Van Huffel, Vanya Van Belle, Johan A. K. Suykens, 2008, ESANN.

Block term decomposition for modelling epileptic seizures

Wim Van Paesschen, Sabine Van Huffel, Maarten De Vos, 2014, EURASIP J. Adv. Signal Process..

Utility metric for unsupervised feature selection

Sabine Van Huffel, Alexander Bertrand, Carolina Varon, 2021, PeerJ Comput. Sci..

Nonnegative Canonical Polyadic Decomposition for Tissue-Type Differentiation in Gliomas

S. Van Huffel, D. M. Sima, H. N. Bharath, 2017, IEEE Journal of Biomedical and Health Informatics.

Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty

S. Huffel, F. Maes, R. Wirix-Speetjens, 2022, Frontiers in Robotics and AI.

A simulation study of sample size demonstrated the importance of the number of events per variable to develop prediction models in clustered data.

S Van Huffel, D Timmerman, W Bouwmeester, 2015, Journal of clinical epidemiology.

Detection of Obstructive Sleep Apnea by Empirical Mode Decomposition on Tachogram

S. Van Huffel, Sergio Cerutti, Martin O. Mendez, 2009 .

White Matter Fiber-Bundle Analysis Using Non-negative Tensor Factorization

Frederik Maes, Sabine Van Huffel, Claudio Stamile, 2016, ICIAR.

Tensor based tumor tissue type differentiation using magnetic resonance spectroscopic imaging

Sabine Van Huffel, Lieven De Lathauwer, Uwe Himmelreich, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Automatic Removal of Ocular Artifacts in the EEG without an EOG Reference Channel

W. De Clercq, W. Van Paesschen, S. Van Huffel, 2006, Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006.

ECG Artifact Removal from Surface EMG Signals by Combining Empirical Mode Decomposition and Independent Component Analysis

Sabine Van Huffel, Thierry Dutoit, Stéphanie Devuyst, 2011, BIOSIGNALS.

Short-Term Prognostic Index for Breast Cancer: NPI or Lpi

S. Huffel, V. Van Belle, P. Neven, 2007, Pathology research international.

Artifact Detection of Wrist Photoplethysmograph Signals

Wim Van Paesschen, Sabine Van Huffel, Jesús Lázaro, 2018, BIOSIGNALS.

Biology and prognosis by age of primary operable breast cancer.

Patrick Neven, S. Van Huffel, Frédéric Amant, 2009 .

Classification of brain tumours using short echo time 1H MR spectra.

J. Suykens, S. Huffel, S. Van Huffel, 2004, Journal of magnetic resonance.

Which extrauterine pelvic masses are difficult to correctly classify as benign or malignant on the basis of ultrasound findings and is there a way of making a correct diagnosis?

S. Huffel, D. Jurkovic, D. Timmerman, 2006, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

On the computation of the multivariate structured total least squares estimator

Sabine Van Huffel, Alexander Kukush, Ivan Markovsky, 2004, Numer. Linear Algebra Appl..

A fast algorithm for subspace state-space system identification via exploitation of the displacement structure

S. Huffel, P. Dooren, D. Kressner, 2001 .

Genomics and Metabolomics Research for Brain Tumour Diagnosis Based on Machine Learning

Sabine Van Huffel, Alfons Juan-Císcar, Juan Miguel García-Gómez, 2007, IWANN.

Modelling of Magnetic Resonance Spectra Using Mixtures for Binned and Truncated Data

Sabine Van Huffel, Alfons Juan-Císcar, Juan Miguel García-Gómez, 2007, IbPRIA.

HealthAgents : Distributed Multi-Agent Brain Tumour Diagnosis and Prognosis

Theodoros N. Arvanitis, S. Huffel, M. Robles, 2007 .

Fast nosologic imaging of the brain.

S Van Huffel, M De Vos, T Laudadio, 2007, Journal of magnetic resonance.

The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification.

A. W. Simonetti, J. Suykens, S. Huffel, 2005, Journal of magnetic resonance.

Using Bayesian neural networks with ARD input selection to detect malignant ovarian masses prior to surgery

Sabine Van Huffel, Dirk Timmerman, Ian T. Nabney, 2008, Neural Computing and Applications.

Different quantification algorithms may lead to different results: a comparison using proton MRS lipid signals

S. Huffel, D. Sima, P. Marzola, 2014, NMR in biomedicine.

Tamoxifen metabolism and efficacy in breast cancer – a prospective multicentre trial

S. Huffel, D. Lambrechts, R. Paridaens, 2020 .

A mixed effects least squares support vector machine model for classification of longitudinal data

Sabine Van Huffel, Johan A. K. Suykens, Geert Molenberghs, 2012, Comput. Stat. Data Anal..

Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines

Sabine Van Huffel, Johan A. K. Suykens, Dirk Timmerman, 2003, AIME.

Evaluation of a Multichannel Non-Contact ECG System and Signal Quality Algorithms for Sleep Apnea Detection and Monitoring

Sabine Van Huffel, Chris Van Hoof, Robert Puers, 2018, Sensors.

Tensor-basedECG Signal Processing Applied to Atrial Fibrillation Detection

Sabine Van Huffel, Lieven De Lathauwer, Sibasankar Padhy, 2018, 2018 52nd Asilomar Conference on Signals, Systems, and Computers.

Adnexal masses difficult to classify as benign or malignant using subjective assessment of gray‐scale and Doppler ultrasound findings: logistic regression models do not help

S. Huffel, D. Timmerman, L. Valentin, 2011, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

Ovarian cancer prediction in adnexal masses using ultrasound‐based logistic regression models: a temporal and external validation study by the IOTA group

S Van Huffel, D Timmerman, I Vergote, 2010, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

Multiparametric Non-Negative Matrix Factorization for Longitudinal Variations Detection in White-Matter Fiber Bundles

Sabine Van Huffel, Frederik Maes, François Cotton, 2017, IEEE Journal of Biomedical and Health Informatics.

A spline-based tool to assess and visualize the calibration of multiclass risk predictions

S. Huffel, T. Bourne, D. Timmerman, 2015, J. Biomed. Informatics.

Pulse Oximetry Markers for Cardiovascular Disease in Sleep Apnea

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2019, 2019 Computing in Cardiology (CinC).

Differences in the cerebral hemodynamics regulation mechanisms of premature infants with intra-ventricular hemorrhage assessed by means of phase rectified signal averaging

Sabine Van Huffel, Carolina Varon, Gunnar Naulaers, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Handling Unbalanced Data in Nocturnal Epileptic Seizure Detection using Accelerometers

Sabine Van Huffel, Bart Vanrumste, Peter Karsmakers, 2013, ICPRAM.

Intravenous contrast ultrasound examination using contrast‐tuned imaging (CnTI™) and the contrast medium SonoVue® for discrimination between benign and malignant adnexal masses with solid components

S. Huffel, V. Van Belle, D. Timmerman, 2009, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

Multi-sparse signal recovery for compressive sensing

Sabine Van Huffel, Maarten De Vos, Yipeng Liu, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Evaluation of a Continuous ECG Quality Indicator Based on the Autocorrelation Function

Sabine Van Huffel, Jonathan Moeyersons, Carolina Varon, 2018, 2018 Computing in Cardiology Conference (CinC).

Recognition of Physical Activities from a Single Arm-Worn Accelerometer: A Multiway Approach

Sabine Van Huffel, Lieven Billiet, Thijs Willem Swinnen, 2018, Informatics.

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI

F. Maes, S. Van Huffel, U. Himmelreich, 2016, NeuroImage: Clinical.

Improved method for accurate and efficient quantification of MRS data with use of prior knowledge

S. Huffel, L. Vanhamme, A. Boogaart, 1997, Journal of magnetic resonance.

Risk of malignancy in unilocular cysts: a study of 1148 adnexal masses classified as unilocular cysts at transvaginal ultrasound and review of the literature

S. Huffel, D. Jurkovic, D. Timmerman, 2013, Ultrasound in Obstetrics and Gynecology.

Java-based framework for processing and displaying short-echo-time magnetic resonance spectroscopy signals

Sabine Van Huffel, Jan Luts, Philippe Lemmerling, 2007, Comput. Methods Programs Biomed..

Modeling the macromolecular background in Nuclear Magnetic Resonance spectroscopic signals

S. Huffel, D. Sima, A. M. R. Díaz, 2009 .

Frequency-selective quantification of short-echo time Magnetic Resonance spectra

Sabine Van Huffel, Diana Maria Sima, Jean-Baptiste Poullet, 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

Assessment of Pain Expression in Infant Cry Signals Using Empirical Mode Decomposition

S Van Huffel, Van den Bergh, B Mijović, 2010, Methods of Information in Medicine.

The filtering approach to solvent peak suppression in MRS: a critical review.

S. Huffel, J. Antoine, S. Van Huffel, 2001, Journal of magnetic resonance.

Fast Removal of Residual Water in Proton Spectra.

S. Huffel, L. Vanhamme, R. Fierro, 1998, Journal of magnetic resonance.

Departement Elektrotechniek ESAT-SISTA / TR 2004-44 Total Least Squares and Errors-in-Variables Modeling : Bridging the Gap between Statistics , Computational Mathematics and Engineering 1

S. Huffel, 2007 .

Journal of Quantitative Analysis in Sports The Curse of Scoreless Draws in Soccer : The Relationship with a Team ' s Offensive , Defensive , and Overall Performance

Sabine Van Huffel, Tim Smits, Ben Van Calster, 2011 .

Muscle and eye movement artifact removal prior to EEG source localization

R. Van de Walle, I. Lemahieu, H. Hallez, 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

ECG artefact detection using ensemble decision trees

Sabine Van Huffel, Jonathan Moeyersons, Carolina Varon, 2017, 2017 Computing in Cardiology (CinC).

The pedicle artery sign based on sonography with color Doppler imaging can replace second‐stage tests in women with abnormal vaginal bleeding

S. Huffel, D. Timmerman, S. Van Huffel, 2003, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

Adding a single CA 125 measurement to ultrasound imaging performed by an experienced examiner does not improve preoperative discrimination between benign and malignant adnexal masses

S. Huffel, T. Bourne, B. van Calster, 2009, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

Corrigendum: Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty

S. Huffel, F. Maes, R. Wirix-Speetjens, 2022, Frontiers in Robotics and AI.

Damping Factor Constraints and Metabolite Profile Selection Influence Magnetic Resonance Spectroscopy Data Quantification

Sabine Van Huffel, Uwe Himmelreich, Diana Maria Sima, 2011, BIOSIGNALS.

Time-domain spectroscopic quantitation

S. Huffel, P. Hecke, L. Vanhamme, 2002 .

Subspace-based parameter estimation of exponentially damped sinusoids using prior knowledge of frequency and phase

Sabine Van Huffel, Hua Chen, Henricus P. A. van den Boom, 1997, Signal Process..

Improved methods for exponential parameter estimation in the presence of known poles and noise

Sabine Van Huffel, Joos Vandewalle, Hua Chen, 1997, IEEE Trans. Signal Process..

Improved exponential data modeling with frequency prior-knowledge

S. Huffel, I. Dologlou, 1996 .

The Cardiorespiratory Graph in Sleep Apnea and Associated Comorbidities

Sabine Van Huffel, Carolina Varon, Dries Testelmans, 2018, 2018 Computing in Cardiology Conference (CinC).

Sleep apnea classification using least-squares support vector machines on single lead ECG

Sabine Van Huffel, Johan A. K. Suykens, Carolina Varon, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Journal of Neuroengineering and Rehabilitation Open Access Review on Solving the Forward Problem in Eeg Source Analysis

S. Huffel, S. Fabri, A. Vergult, 2022 .

Variable rate speech compression based on exact modeling and waveform vector quantization

Sabine Van Huffel, Philippe Lemmerling, I Dologlou, 1998 .

Fast Structured Total Least Squares Algorithm for Solving the Basic Deconvolution Problem

S. Huffel, N. Mastronardi, P. Lemmerling, 2000, SIAM J. Matrix Anal. Appl..

PyECG: A software tool for the analysis of the QT interval in the electrocardiogram

Sabine Van Huffel, Alexander A. Suárez León, Carolina Varon, 2019 .

T-wave end detection using neural networks and Support Vector Machines

Sabine Van Huffel, Carlos R. Vázquez-Seisdedos, Alexander A. Suárez León, 2018, Comput. Biol. Medicine.

Separating respiratory influences from the tachogram: Methods and their sensitivity to the type of respiratory signal

Sabine Van Huffel, Luca Faes, Carolina Varon, 2014, Computing in Cardiology 2014.

Analysis of non-linear respiratory influences on sleep apnea classification

Sabine Van Huffel, Carolina Varon, Alexander Caicedo, 2014, Computing in Cardiology 2014.

Detection of epileptic seizures from single lead ECG by means of phase rectified signal averaging

Sabine Van Huffel, Lieven Lagae, Carolina Varon, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Tensor-based detection of T wave alternans using ECG

Sabine Van Huffel, Rik Willems, Griet Goovaerts, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Tensor-based detection of T wave alternans in multilead ECG signals

Sabine Van Huffel, Carolina Varon, Rik Willems, 2014, Computing in Cardiology 2014.

Frequency-selective quantification of biomedical magnetic resonance spectroscopy data.

S. Huffel, R. Pintelon, S. Van Huffel, 2000, Journal of magnetic resonance.

Automatic Artifact Removal of Resting-State fMRI with Deep Neural Networks

S. Huffel, C. Chatzichristos, Christos Theodoropoulos, 2020, 2021 29th European Signal Processing Conference (EUSIPCO).

High-performance numerical software for control

V. Sima, A. Varga, S. Hammarling, 2004, IEEE Control Systems.

Automating Muscle Artifact Removal in Ictal EEG

Wim Van Paesschen, Sabine Van Huffel, Anneleen Vergult, 2005 .

Van spectroscopisch signaal tot klinische diagnose

Sabine Van Huffel, Paul Van Hecke, Leentje Vanhamme, 2005 .

Independent component analysis of single trial evoked brain reponses : is it reliable ?

Wim Van Paesschen, Sabine Van Huffel, Karen O. Egiazarian, 2005 .

Classification of Brain Tumors Based on Magnetic Resonance Spectroscopy (Classificatie van hersentumoren op basis van magnetische resonantie spectroscopie)

S. Huffel, J. Luts, B. Celda, 2010 .

A Comparison of Machine Learning Approaches for Classifying Multiple Sclerosis Courses Using MRSI and Brain Segmentations

Diana Maria Sima, Sabine Van Huffel, Claudio Stamile, 2017, ICANN.

Data Quality Assessment of Capacitively-Coupled ECG Signals

Amalia Villa Gómez, John F. Morales, S. Huffel, 2019, 2019 Computing in Cardiology (CinC).

Inferior and anterior QRS fragmentation have different prognostic value in patients who received an implantable defibrillator in primary prevention of sudden cardiac death.

S Van Huffel, S. Huffel, S. Van Huffel, 2017, International journal of cardiology.

Iterative algorithms for computing the singular subspace of a matrix associated with its smallest singular values

Sabine Van Huffel, S. Huffel, 1991 .