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Celine Vens

Showing results (21-30 of 36) with videos related to

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Acta Anaesthesiologica Scandinavica|April 26, 2026
A Wireless Photoplethysmography Chest Patch for Continuous Vital Sign Monitoring: A Clinical Validation Study in Intensive Care PatientsLouis Van Slambrouck, Lucy Van Kleunen, Charlotte Van den Storme, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 21, 2022
Online Extra Trees RegressorSaulo Martiello Mastelini, Felipe Kenji Nakano, Celine Vens, et al.
Plos Computational Biology|April 24, 2018
A machine learning based framework to identify and classify long terminal repeat retrotransposonsLeander Schietgat, Celine Vens, Ricardo Cerri, et al.
Intensive Care Medicine Experimental|September 30, 2025
Development and validation of a machine learning model for early prediction of intensive care unit acquired weaknessFelipe Kenji Nakano, Nathalie Van Aerde, Grégoire Coppens, et al.
Behavior Research Methods|July 12, 2022
Comparing the prediction performance of item response theory and machine learning methods on item responses for educational assessmentsJung Yeon Park, Klest Dedja, Konstantinos Pliakos, et al.
Intensive Care Medicine Experimental|October 20, 2025
Correction: Development and validation of a machine learning model for early prediction of intensive care unit acquired weaknessFelipe Kenji Nakano, Nathalie Van Aerde, Gregoire Coppens, et al.
The Journal of Heart and Lung Transplantation : the Official Publication of the International Society for Heart Transplantation|May 14, 2022
Temporal shift and predictive performance of machine learning for heart transplant outcomesRobert J H Miller, František Sabovčik, Nicholas Cauwenberghs, et al.
Bioinformatics (Oxford, England)|February 2, 2015
Learning HMMs for nucleotide sequences from amino acid alignmentsCarlos N Fischer, Claudia M A Carareto, Renato A C dos Santos, et al.
Nature Communications|June 12, 2024
CHIT1 at diagnosis predicts faster disability progression and reflects early microglial activation in multiple sclerosisJarne Beliën, Stijn Swinnen, Robbe D'hondt, et al.
Computer Methods and Programs in Biomedicine|April 13, 2024
Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admissionFelipe Kenji Nakano, Karolijn Dulfer, Ilse Vanhorebeek, et al.
Pageof 4

Showing results (21-30 of 36) with videos related to

Sort By:
Pageof 4
Acta Anaesthesiologica Scandinavica|April 26, 2026
A Wireless Photoplethysmography Chest Patch for Continuous Vital Sign Monitoring: A Clinical Validation Study in Intensive Care PatientsLouis Van Slambrouck, Lucy Van Kleunen, Charlotte Van den Storme, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 21, 2022
Online Extra Trees RegressorSaulo Martiello Mastelini, Felipe Kenji Nakano, Celine Vens, et al.
Plos Computational Biology|April 24, 2018
A machine learning based framework to identify and classify long terminal repeat retrotransposonsLeander Schietgat, Celine Vens, Ricardo Cerri, et al.
Intensive Care Medicine Experimental|September 30, 2025
Development and validation of a machine learning model for early prediction of intensive care unit acquired weaknessFelipe Kenji Nakano, Nathalie Van Aerde, Grégoire Coppens, et al.
Behavior Research Methods|July 12, 2022
Comparing the prediction performance of item response theory and machine learning methods on item responses for educational assessmentsJung Yeon Park, Klest Dedja, Konstantinos Pliakos, et al.
Intensive Care Medicine Experimental|October 20, 2025
Correction: Development and validation of a machine learning model for early prediction of intensive care unit acquired weaknessFelipe Kenji Nakano, Nathalie Van Aerde, Gregoire Coppens, et al.
The Journal of Heart and Lung Transplantation : the Official Publication of the International Society for Heart Transplantation|May 14, 2022
Temporal shift and predictive performance of machine learning for heart transplant outcomesRobert J H Miller, František Sabovčik, Nicholas Cauwenberghs, et al.
Bioinformatics (Oxford, England)|February 2, 2015
Learning HMMs for nucleotide sequences from amino acid alignmentsCarlos N Fischer, Claudia M A Carareto, Renato A C dos Santos, et al.
Nature Communications|June 12, 2024
CHIT1 at diagnosis predicts faster disability progression and reflects early microglial activation in multiple sclerosisJarne Beliën, Stijn Swinnen, Robbe D'hondt, et al.
Computer Methods and Programs in Biomedicine|April 13, 2024
Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admissionFelipe Kenji Nakano, Karolijn Dulfer, Ilse Vanhorebeek, et al.
Pageof 4