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| 85 |       | Jan Luts, Geert Molenberghs, Geert Verbeke, Sabine Van Huffel, Johan A. K. Suykens: A mixed effects least squares support vector machine model for classification of longitudinal data. Computational Statistics & Data Analysis 56(3): 611-628 (2012) |
| 84 | | Devy Widjaja, Carolina Varon, Alexander Dorado, Johan A. K. Suykens, Sabine Van Huffel: Application of Kernel Principal Component Analysis for Single-Lead-ECG-Derived Respiration. IEEE Trans. Biomed. Engineering 59(4): 1169-1176 (2012) |
| 77 | | Borbala Hunyadi, Maarten De Vos, Marco Signoretto, Johan A. K. Suykens, Wim Van Paesschen, Sabine Van Huffel: Automatic Seizure Detection Incorporating Structural Information. ICANN (1) 2011: 233-240 |
| 76 | | Vanya Van Belle, Kristiaan Pelckmans, Sabine Van Huffel, Johan A. K. Suykens: Support vector methods for survival analysis: a comparison between ranking and regression approaches. Artificial Intelligence in Medicine 53(2): 107-118 (2011) |
| 75 | | Vanya Van Belle, Kristiaan Pelckmans, Sabine Van Huffel, Johan A. K. Suykens: Improved performance on high-dimensional survival data by application of Survival-SVM. Bioinformatics 27(1): 87-94 (2011) |
| 74 | | Geert J. Postma, Jan Luts, Albert J. Idema, Margarida Julià-Sapé, Àngel Moreno-Torres, Witek Gajewicz, Johan A. K. Suykens, Arend Heerschap, Sabine Van Huffel, Lutgarde M. C. Buydens: On the relevance of automatically selected single-voxel MRS and multimodal MRI and MRSI features for brain tumour differentiation. Comp. in Bio. and Med. 41(2): 87-97 (2011) |
| 73 | | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: Learning Transformation Models for Ranking and Survival Analysis. Journal of Machine Learning Research 12: 819-862 (2011) |
| 67 | | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: On the use of a clinical kernel in survival analysis. ESANN 2010 |
| 61 | | Jan Luts, Johan A. K. Suykens, Sabine Van Huffel, Teresa Laudadio, Sofie Van Cauter, Uwe Himmelreich, Enrique Molla, Jose Piquer, M. Carmen Martinez-Bisbal, Bernardo Celda: Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI. CBMS 2009: 1-8 |
| 60 | | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: MINLIP: Efficient Learning of Transformation Models. ICANN (1) 2009: 60-69 |
| 59 | | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints. IWANN (1) 2009: 65-72 |
| 50 | | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: Survival SVM: a practical scalable algorithm. ESANN 2008: 89-94 |
| 45 | | Ben Van Calster, Jan Luts, Johan A. K. Suykens, George Condous, Tom Bourne, Dirk Timmerman, Sabine Van Huffel: Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression. ICANN (2) 2007: 139-148 |
| 41 | | Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sabine Van Huffel: A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection. Artificial Intelligence in Medicine 40(2): 87-102 (2007) |
| 34 | | Chuan Lu, Andy Devos, Johan A. K. Suykens, Carles Arús, Sabine Van Huffel: Bagging Linear Sparse Bayesian Learning Models for Variable Selection in Cancer Diagnosis. IEEE Transactions on Information Technology in Biomedicine 11(3): 338-347 (2007) |
| 22 | | Lukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, Franklyn A. Howe, Carles Majós, Àngel Moreno-Torres, M. Van Der Graaf, Anne Rosemary Tate, Carles Arús, Sabine Van Huffel: Brain tumor classification based on long echo proton MRS signals. Artificial Intelligence in Medicine 31(1): 73-89 (2004) |
| 20 | | Chuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Dirk Timmerman, Ignace Vergote: Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines. AIME 2003: 219-228 |
| 19 | | Chuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Ignace Vergote, Dirk Timmerman: Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines. Artificial Intelligence in Medicine 28(3): 281-306 (2003) |
| 17 |  | Lukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, Sabine Van Huffel, Anne Rosemary Tate, Carles Majós, Carles Arús: The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals. ESANN 2002: 131-136 |
| 16 | | Lieveke Ameye, Chuan Lu, Lukas Lukas, Jos De Brabanter, Johan A. K. Suykens, Sabine Van Huffel, Hans Daniels, Gunnar Naulaers, Hugo Devlieger: Prediction of mental development of preterm newborns at birth time using LS-SVM. ESANN 2002: 167-172 |
Selection of 20 from 92 records - Sabine Van Huffel has 172 coauthors
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