Ghent University Academic Bibliography

Your filters: cql: author="Becker, Thijs" or (type any "bookEditor issueEditor" and editor="Becker, Thijs")

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Evaluating feature attribution methods in the image domain

Arne Gevaert (UGent) , Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie (UGent) and Yvan Saeys (UGent)

(2024) MACHINE LEARNING.
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- A2
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Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study

Edward De Brouwer, Thijs Becker, Lorin Werthen-Brabants (UGent) , Pieter Dewulf (UGent) , Dimitrios Iliadis (UGent) , Cathérine Dekeyser (UGent) , Guy Laureys (UGent) , Bart Van Wijmeersch, Veronica Popescu, Tom Dhaene (UGent) , et al.

(2024) PLOS DIGITAL HEALTH. 3(7).
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- Miscellaneous
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Evaluating feature attribution methods in the image domain

Arne Gevaert (UGent) , Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie (UGent) and Yvan Saeys (UGent)

(2022) ArXiv.
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- Miscellaneous
Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study

Edward De Brouwer, Thijs Becker, Lorin Werthen-Brabants (UGent) , Pieter Dewulf (UGent) , Dimitrios Iliadis (UGent) , Cathérine Dekeyser (UGent) , Guy Laureys (UGent) , Bart Van Wijmeersch, Veronica Popescu, Tom Dhaene (UGent) , et al.

(2022) MedRXiv.
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Deciphering the morphology of motor evoked potentials

Jan Yperman, Thijs Becker, Dirk Valkenborg, Niels Hellings, Melissa Cambron, Dominique Dive, Guy Laureys (UGent) , Veronica Popescu, Bart Van Wijmeersch and Liesbet M. Peeters

(2020) FRONTIERS IN NEUROINFORMATICS. 14.

Academic Bibliography

Evaluating feature attribution methods in the image domain

Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study

Evaluating feature attribution methods in the image domain

Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study

Deciphering the morphology of motor evoked potentials

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