Thijs Becker

发表

Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis

V. Popescu, J. Yperman, N. Hellings, 2020, BMC Neurology.

Motor evoked potentials for multiple sclerosis, a multiyear follow-up dataset

V. Popescu, J. Yperman, B. van Wijmeersch, 2022, Scientific data.

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

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

Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression

Ludwig Kappos, Edward De Brouwer, Thijs Becker, 2021, Comput. Methods Programs Biomed..

Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis

Thijs Becker, Liesbet Peeters, Dirk Valkenborg, 2019, bioRxiv.

Corrigendum to Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression: [Computer Methods and Programs in Biomedicine, Volume 208, (September 2021) 106180]

Ludwig Kappos, Edward De Brouwer, Thijs Becker, 2021, Comput. Methods Programs Biomed..

Evaluating Feature Attribution Methods in the Image Domain

Y. Saeys, T. D. Bie, D. Valkenborg, 2022, ArXiv.

Longitudinal modeling of MS patient trajectories improves predictions of disability progression pdf

Edward De Brouwer, Thijs Becker, Yves Moreau, 2020, ArXiv.

Deciphering the Morphology of Motor Evoked Potentials

Thijs Becker, Bart Van Wijmeersch, Dirk Valkenborg, 2020, Frontiers in Neuroinformatics.

Post Training Uncertainty Calibration Of Deep Networks For Medical Image Segmentation

Matthew B. Blaschko, Thijs Becker, Jeroen Bertels, 2020, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

Bayesian optimization of hyper-parameters in reservoir computing pdf

Thijs Becker, Jan Yperman, J. Yperman, 2016, ArXiv.