Tom Van Steenkiste

According to our database, Tom Van Steenkiste authored at least 15 papers between 2016 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

Portable Detection of Apnea and Hypopnea Events Using Bio-Impedance of the Chest and Deep Learning.

Tom Van Steenkiste, Willemijn Groenendaal, Pauline Dreesen, Seulki Lee, Susie Klerkx, Ruben de Francisco, Dirk Deschrijver, Tom Dhaene

IEEE J. Biomed. Health Informatics, 2020

Interpretable Epilepsy Detection in Routine, Interictal EEG Data using Deep Learning.

Thomas Uyttenhove, Aren Maes, Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene

Proceedings of the Machine Learning for Health Workshop, 2020

2019

Automated Sleep Apnea Detection in Raw Respiratory Signals Using Long Short-Term Memory Neural Networks.

Tom Van Steenkiste, Willemijn Groenendaal, Dirk Deschrijver, Tom Dhaene

IEEE J. Biomed. Health Informatics, 2019

ALBATROS: adaptive line-based sampling trajectories for sequential measurements.

Tom Van Steenkiste, Joachim van der Herten, Dirk Deschrijver, Tom Dhaene

Eng. Comput., 2019

Generating an Explainable ECG Beat Space With Variational Auto-Encoders.

Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene

CoRR, 2019

Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks.

Tom Van Steenkiste, Joeri Ruyssinck, Leen De Baets, Johan Decruyenaere, Filip De Turck, Femke Ongenae, Tom Dhaene

Artif. Intell. Medicine, 2019

Learning To Forget: Design of Experiments for Line-Based Bayesian Optimization in Dynamic Environments.

Jens Jocqué, Tom Van Steenkiste, Pieter Stroobant, Rémi Delanghe, Dirk Deschrijver, Tom Dhaene

Proceedings of the 2019 Winter Simulation Conference, 2019

Sensor Fusion using Backward Shortcut Connections for Sleep Apnea Detection in Multi-Modal Data.

Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene

Proceedings of the Machine Learning for Health Workshop, 2019

Interpretable ECG Beat Embedding using Disentangled Variational Auto-Encoders.

Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene

Proceedings of the 32nd IEEE International Symposium on Computer-Based Medical Systems, 2019

Disentangled Variational Auto-Encoders for Explaining ECG Beat Embeddings.

Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

A Study of Early Sepsis Detection Models Based on Multivariate Medical Time Series.

Aren Maes, Tom Van Steenkiste, Tom Dhaene, Dirk Deschrijver

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

Continuous Exploitative Measurement Trajectories Using Bayesian Optimisation.

Rémi Delanghe, Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression.

Tom Van Steenkiste, Joeri Ruyssinck, Olivier Janssens, Baptist Vandersmissen, Florian Vandecasteele, Pieter Devolder, Eric Achten, Sofie Van Hoecke, Dirk Deschrijver, Tom Dhaene

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Systematic Comparison of Respiratory Signals for the Automated Detection of Sleep Apnea.

Tom Van Steenkiste, Willemijn Groenendaal, Joeri Ruyssinck, Pauline Dreesen, Susie Klerkx, Christophe Smeets, Ruben de Francisco, Dirk Deschrijver, Tom Dhaene

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2016

Sensitivity analysis of expensive black-box systems using metamodeling.

Tom Van Steenkiste, Joachim van der Herten, Ivo Couckuyt, Tom Dhaene

Proceedings of the Winter Simulation Conference, 2016