Bayesian Networks in Ovarian Cancer Diagnosis: Potentials and Limitations. - Peter Antal; Herman Verrelst; Dirk Timmerman; Sabine Van Huffel; Bart De Moor; Ignace Vergote (CBMS, 2000)

Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines. - Chuan Lu; Tony Van Gestel; Johan A. K. Suykens; Sabine Van Huffel; Dirk Timmerman; Ignace Vergote (AIME, 2003)

Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines. - Chuan Lu; Tony Van Gestel; Johan A. K. Suykens; Sabine Van Huffel; Ignace Vergote; Dirk Timmerman (Artif. Intell. Medicine, 2003)

M@CBETH: Optimizing Clinical Microarray Classification. - Nathalie Pochet; Frizo A. L. Janssens; Frank De Smet; Kathleen Marchal; Ignace Vergote; Johan A. K. Suykens; Bart De Moor (CSB Workshops, 2005)

Classification of Sporadic and BRCA1 Ovarian Cancer Based on a Genome-Wide Study of Copy Number Variations. - Anneleen Daemen; Olivier Gevaert; Karin Leunen; Vanessa Vanspauwen; Geneviève Michils; Eric Legius; Ignace Vergote; Bart De Moor (KES (2), 2008)

Using Bayesian neural networks with ARD input selection to detect malignant ovarian masses prior to surgery. - Ben Van Calster; Dirk Timmerman; Ian T. Nabney; Lil Valentin; Antonia C. Testa; Caroline Van Holsbeke; Ignace Vergote; Sabine Van Huffel (Neural Comput. Appl., 2008)

Supervised Classification of Array CGH Data with HMM-Based Feature Selection. - Anneleen Daemen; Olivier Gevaert; Karin Leunen; Eric Legius; Ignace Vergote; Bart De Moor (Pacific Symposium on Biocomputing, 2009)