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Tom Van Steenkiste
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2020 – today
- 2020
- [j4]Tom Van Steenkiste
, Willemijn Groenendaal
, Pauline Dreesen
, Seulki Lee, Susie Klerkx
, Ruben de Francisco, Dirk Deschrijver
, Tom Dhaene
:
Portable Detection of Apnea and Hypopnea Events Using Bio-Impedance of the Chest and Deep Learning. IEEE J. Biomed. Health Informatics 24(9): 2589-2598 (2020) - [c10]Thomas Uyttenhove, Aren Maes, Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Interpretable Epilepsy Detection in Routine, Interictal EEG Data using Deep Learning. ML4H@NeurIPS 2020: 355-366
2010 – 2019
- 2019
- [j3]Tom Van Steenkiste
, Joeri Ruyssinck
, Leen De Baets, Johan Decruyenaere, Filip De Turck
, Femke Ongenae, Tom Dhaene:
Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks. Artif. Intell. Medicine 97: 38-43 (2019) - [j2]Tom Van Steenkiste
, Joachim van der Herten, Dirk Deschrijver
, Tom Dhaene:
ALBATROS: adaptive line-based sampling trajectories for sequential measurements. Eng. Comput. 35(2): 537-550 (2019) - [j1]Tom Van Steenkiste
, Willemijn Groenendaal
, Dirk Deschrijver
, Tom Dhaene
:
Automated Sleep Apnea Detection in Raw Respiratory Signals Using Long Short-Term Memory Neural Networks. IEEE J. Biomed. Health Informatics 23(6): 2354-2364 (2019) - [c9]Rémi Delanghe, Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Continuous Exploitative Measurement Trajectories Using Bayesian Optimisation. BNAIC/BENELEARN 2019 - [c8]Aren Maes, Tom Van Steenkiste, Tom Dhaene, Dirk Deschrijver:
A Study of Early Sepsis Detection Models Based on Multivariate Medical Time Series. BNAIC/BENELEARN 2019 - [c7]Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Disentangled Variational Auto-Encoders for Explaining ECG Beat Embeddings. BNAIC/BENELEARN 2019 - [c6]Tom Van Steenkiste, Dirk Deschrijver
, Tom Dhaene:
Interpretable ECG Beat Embedding using Disentangled Variational Auto-Encoders. CBMS 2019: 373-378 - [c5]Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Sensor Fusion using Backward Shortcut Connections for Sleep Apnea Detection in Multi-Modal Data. ML4H@NeurIPS 2019: 112-125 - [c4]Jens Jocqué, Tom Van Steenkiste, Pieter Stroobant, Rémi Delanghe, Dirk Deschrijver
, Tom Dhaene:
Learning To Forget: Design of Experiments for Line-Based Bayesian Optimization in Dynamic Environments. WSC 2019: 656-667 - [i3]Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Generating an Explainable ECG Beat Space With Variational Auto-Encoders. CoRR abs/1911.04898 (2019) - [i2]Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Sensor Fusion using Backward Shortcut Connections for Sleep Apnea Detection in Multi-Modal Data. CoRR abs/1912.06879 (2019) - 2018
- [c3]Tom Van Steenkiste, Willemijn Groenendaal, Joeri Ruyssinck, Pauline Dreesen, Susie Klerkx, Christophe Smeets, Ruben de Francisco, Dirk Deschrijver
, Tom Dhaene:
Systematic Comparison of Respiratory Signals for the Automated Detection of Sleep Apnea. EMBC 2018: 449-452 - [c2]Tom Van Steenkiste, Joeri Ruyssinck, Olivier Janssens, Baptist Vandersmissen, Florian Vandecasteele, Pieter Devolder
, Eric Achten, Sofie Van Hoecke, Dirk Deschrijver
, Tom Dhaene:
Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression. EMBC 2018: 674-677 - 2017
- [i1]Tom Van Steenkiste, Joachim van der Herten, Ivo Couckuyt, Tom Dhaene:
Sensitivity Analysis of Expensive Black-Box Systems Using Metamodeling. CoRR abs/1702.00650 (2017) - 2016
- [c1]Tom Van Steenkiste
, Joachim van der Herten
, Ivo Couckuyt, Tom Dhaene:
Sensitivity analysis of expensive black-box systems using metamodeling. WSC 2016: 578-589
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