| Appliance classification using VI trajectories and convolutional neural networks L De Baets, J Ruyssinck, C Develder, T Dhaene, D Deschrijver Energy and Buildings 158, 32-36, 2018 | 235 | 2018 |
| Comprehensive feature selection for appliance classification in NILM N Sadeghianpourhamami, J Ruyssinck, D Deschrijver, T Dhaene, ... Energy and Buildings 151, 98-106, 2017 | 193 | 2017 |
| Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores R Houthooft, J Ruyssinck, J van der Herten, S Stijven, I Couckuyt, ... Artificial intelligence in medicine 63 (3), 191-207, 2015 | 107 | 2015 |
| On the Bayesian optimization and robustness of event detection methods in NILM L De Baets, J Ruyssinck, C Develder, T Dhaene, D Deschrijver Energy and Buildings 145, 57-66, 2017 | 87 | 2017 |
| NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms J Ruyssinck, VA Huynh-Thu, P Geurts, T Dhaene, P Demeester, Y Saeys PLoS One 9 (3), e92709, 2014 | 71 | 2014 |
| Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks T Van Steenkiste, J Ruyssinck, L De Baets, J Decruyenaere, F De Turck, ... Artificial intelligence in medicine 97, 38-43, 2019 | 62 | 2019 |
| Event detection in NILM using cepstrum smoothing L De Baets, J Ruyssinck, D Deschrijver, T Dhaene 3rd International Workshop on Non-Intrusive Load Monitoring, 1-4, 2016 | 37 | 2016 |
| Automated assessment of bone age using deep learning and Gaussian process regression T Van Steenkiste, J Ruyssinck, O Janssens, B Vandersmissen, ... 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 33 | 2018 |
| Random survival forests for predicting the bed occupancy in the intensive care unit J Ruyssinck, J van der Herten, R Houthooft, F Ongenae, I Couckuyt, ... Computational and mathematical methods in medicine 2016 (1), 7087053, 2016 | 23 | 2016 |
| Systematic comparison of respiratory signals for the automated detection of sleep apnea T Van Steenkiste, W Groenendaal, J Ruyssinck, P Dreesen, S Klerkx, ... 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 19 | 2018 |
| Data analytics for health and connected care: Ontology, knowledge graph and applications B Steenwinckel, M De Brouwer, M Stojchevska, J Van Der Donckt, J Nelis, ... International Conference on Pervasive Computing Technologies for Healthcare …, 2022 | 15 | 2022 |
| Data-driven optimization of energy efficiency and comfort in an apartment DN Avendano, J Ruyssinck, S Vandekerckhove, S Van Hoecke, ... 2018 international conference on intelligent systems (is), 174-182, 2018 | 13 | 2018 |
| Netter: re-ranking gene network inference predictions using structural network properties J Ruyssinck, P Demeester, T Dhaene, Y Saeys BMC bioinformatics 17, 1-16, 2016 | 13 | 2016 |
| Authenticity analysis of oregano: Development, validation and fitness for use of several food fingerprinting techniques J Van De Steene, J Ruyssinck, JA Fernandez-Pierna, L Vandermeersch, ... Food Research International 162, 111962, 2022 | 12 | 2022 |
| Learning multivariate shapelets with multi-layer neural networks for interpretable time-series classification R Medico, J Ruyssinck, D Deschrijver, T Dhaene Advances in Data Analysis and Classification 15 (4), 911-936, 2021 | 11 | 2021 |
| Positive blood culture detection in time series data using a BiLSTM network L De Baets, J Ruyssinck, T Peiffer, J Decruyenaere, F De Turck, ... arXiv preprint arXiv:1612.00962, 2016 | 11 | 2016 |
| Optimized statistical test for event detection in non-intrusive load monitoring L De Baets, J Ruyssinck, C Develder, T Dhaene, D Deschrijver 2017 IEEE International Conference on Environment and Electrical Engineering …, 2017 | 7 | 2017 |
| Fingerprinting methods for origin and variety assessment of rice: Development, validation and data fusion experiments J Van De Steene, J Ruyssinck, JA Fernandez-Pierna, L Vandermeersch, ... Food Control 151, 109780, 2023 | 6 | 2023 |
| IncGraph: Incremental graphlet counting for topology optimisation R Cannoodt, J Ruyssinck, J Ramon, K De Preter, Y Saeys PloS one 13 (4), e0195997, 2018 | 5 | 2018 |
| Learning multivariate shapelets with multi-layer neural networks R Medico, J Ruyssinck, D Deschrijver, T Dhaene ACDL-Advanced Course on Data Science & Machine Learning, 2018 | 2 | 2018 |
Tom DhaeneGhent University - imecGeverifieerd e-mailadres voor ugent.be
