2008 |
16 | EE | Ben Van Calster,
Sabine Van Huffel,
Dirk Timmerman,
Emma Kirk,
Tom Bourne,
George Condous:
Towards a Clinical Decision Support System for Pregnancies of Unknown Location.
CBMS 2008: 581-583 |
15 | EE | Ben Van Calster,
Dirk Timmerman,
Antonia C. Testa,
Lil Valentin,
Sabine Van Huffel:
Multi-class classification of ovarian tumors.
ESANN 2008: 65-70 |
14 | EE | Ben Van Calster,
Vanya Van Belle,
George Condous,
Tom Bourne,
Dirk Timmerman,
Sabine Van Huffel:
Multi-class AUC metrics and weighted alternatives.
IJCNN 2008: 1390-1396 |
13 | EE | Ben Van Calster,
Dirk Timmerman,
Ian T. Nabney,
Lil Valentin,
Antonia C. Testa,
Caroline Van Holsbeke,
Ignace Vergote,
Sabine Van Huffel:
Using Bayesian neural networks with ARD input selection to detect malignant ovarian masses prior to surgery.
Neural Computing and Applications 17(5-6): 489-500 (2008) |
2007 |
12 | EE | 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 |
11 | EE | M. S. Hane Aung,
Paulo J. G. Lisboa,
Terence A. Etchells,
Antonia C. Testa,
Ben Van Calster,
Sabine Van Huffel,
Lil Valentin,
Dirk Timmerman:
Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy.
ISNN (2) 2007: 1177-1186 |
2006 |
10 | EE | Olivier Gevaert,
Frank De Smet,
Dirk Timmerman,
Yves Moreau,
Bart De Moor:
Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks.
ISMB (Supplement of Bioinformatics) 2006: 184-190 |
2004 |
9 | EE | Peter Antal,
Geert Fannes,
Dirk Timmerman,
Yves Moreau,
Bart De Moor:
Using literature and data to learn Bayesian networks as clinical models of ovarian tumors.
Artificial Intelligence in Medicine 30(3): 257-281 (2004) |
2003 |
8 | EE | 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 |
7 | EE | 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) |
6 | EE | Peter Antal,
Geert Fannes,
Dirk Timmerman,
Yves Moreau,
Bart De Moor:
Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor classification with rejection.
Artificial Intelligence in Medicine 29(1-2): 39-60 (2003) |
2002 |
5 | EE | Peter Antal,
Dirk Timmerman,
Tamás Mészáros,
Tadeusz P. Dobrowiecki:
Domain Knowledge Based Information Retrieval Language: An Application Of Annotated Bayesian Network In Ovarian Cancer Domain.
CBMS 2002: 213-218 |
4 | EE | Stein Aerts,
Peter Antal,
Dirk Timmerman,
Bart De Moor,
Yves Moreau:
Web-based Data Collection for Uterine Adnexal Tumors: A Case Study.
CBMS 2002: 282-287 |
2001 |
3 | EE | Peter Antal,
Geert Fannes,
Bart De Moor,
Joos Vandewalle,
Yves Moreau,
Dirk Timmerman:
Extended Bayesian Regression Models: A Symbiotic Application of Belief Networks and Multilayer Perceptrons for the Classification of Ovarian Tumors.
AIME 2001: 177-187 |
2000 |
2 | EE | Peter Antal,
Herman Verrelst,
Dirk Timmerman,
Sabine Van Huffel,
Bart De Moor,
Ignace Vergote:
Bayesian Networks in Ovarian Cancer Diagnosis: Potentials and Limitations.
CBMS 2000: 103-108 |
1997 |
1 | | Herman Verrelst,
Yves Moreau,
Joos Vandewalle,
Dirk Timmerman:
Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors.
NIPS 1997 |