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Lorin Werthen-Brabants

Showing results (1-10 of 8) with videos related to

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Frontiers in Digital Health|April 8, 2025
The role of trustworthy and reliable AI for multiple sclerosisLorin Werthen-Brabants, Tom Dhaene, Dirk Deschrijver
Scientific Reports|May 6, 2022
Split BiRNN for real-time activity recognition using radar and deep learningLorin Werthen-Brabants, Geethika Bhavanasi, Ivo Couckuyt, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
Convolutional Neural Networks for Apnea Detection from Smartphone Audio Signals: Effect of Window SizeYolanda Castillo-Escario, Lorin Werthen-Brabants, Willemijn Groenendaal, et al.
IEEE Transactions on Bio-Medical Engineering|March 3, 2025
Deep Learning-Based Event Counting for Apnea-Hypopnea Index Estimation Using Recursive Spiking Neural NetworksLorin Werthen-Brabants, Yolanda Castillo-Escario, Willemijn Groenendaal, et al.
Frontiers in Immunology|April 30, 2026
Data-driven hypothesis discovery from disease trajectories in multiple sclerosisNiels Jodts, Lorin Werthen-Brabants, Sofie Aerts, et al.
Frontiers in Neuroscience|November 14, 2025
Leveraging hand-crafted radiomics on multicenter FLAIR MRI for predicting disability worsening in people with multiple sclerosisHamza Khan, Henry C Woodruff, Diana L Giraldo, et al.
Frontiers in Immunology|March 27, 2026
Combining magnetic resonance imaging and evoked potentials enhances machine learning prediction of multiple sclerosis disability worseningSofie Aerts, Lorin Werthen-Brabants, Hamza Khan, et al.
PLOS Digital Health|July 25, 2024
Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center studyEdward De Brouwer, Thijs Becker, Lorin Werthen-Brabants, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Frontiers in Digital Health|April 8, 2025
The role of trustworthy and reliable AI for multiple sclerosisLorin Werthen-Brabants, Tom Dhaene, Dirk Deschrijver
Scientific Reports|May 6, 2022
Split BiRNN for real-time activity recognition using radar and deep learningLorin Werthen-Brabants, Geethika Bhavanasi, Ivo Couckuyt, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
Convolutional Neural Networks for Apnea Detection from Smartphone Audio Signals: Effect of Window SizeYolanda Castillo-Escario, Lorin Werthen-Brabants, Willemijn Groenendaal, et al.
IEEE Transactions on Bio-Medical Engineering|March 3, 2025
Deep Learning-Based Event Counting for Apnea-Hypopnea Index Estimation Using Recursive Spiking Neural NetworksLorin Werthen-Brabants, Yolanda Castillo-Escario, Willemijn Groenendaal, et al.
Frontiers in Immunology|April 30, 2026
Data-driven hypothesis discovery from disease trajectories in multiple sclerosisNiels Jodts, Lorin Werthen-Brabants, Sofie Aerts, et al.
Frontiers in Neuroscience|November 14, 2025
Leveraging hand-crafted radiomics on multicenter FLAIR MRI for predicting disability worsening in people with multiple sclerosisHamza Khan, Henry C Woodruff, Diana L Giraldo, et al.
Frontiers in Immunology|March 27, 2026
Combining magnetic resonance imaging and evoked potentials enhances machine learning prediction of multiple sclerosis disability worseningSofie Aerts, Lorin Werthen-Brabants, Hamza Khan, et al.
PLOS Digital Health|July 25, 2024
Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center studyEdward De Brouwer, Thijs Becker, Lorin Werthen-Brabants, et al.
Pageof 1