Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors. - Herman Verrelst; Yves Moreau; Joos Vandewalle; Dirk Timmerman (NIPS, 1997)

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)

Extended Bayesian Regression Models: A Symbiotic Application of Belief Networks and Multilayer Perceptrons for the Classification of Ovarian Tumors. - Peter Antal; Geert Fannes; Bart De Moor; Joos Vandewalle; Yves Moreau; Dirk Timmerman (AIME, 2001)

Web-based Data Collection for Uterine Adnexal Tumors: A Case Study. - Stein Aerts; Peter Antal; Dirk Timmerman; Bart De Moor; Yves Moreau (CBMS, 2002)

Domain Knowledge Based Information Retrieval Language: An Application Of Annotated Bayesian Network In Ovarian Cancer Domain. - Peter Antal; Dirk Timmerman; Tamás Mészáros 003; Tadeusz P. Dobrowiecki (CBMS, 2002)

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)

Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor classification with rejection. - Peter Antal; Geert Fannes; Dirk Timmerman; Yves Moreau; Bart De Moor (Artif. Intell. Medicine, 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)

Using literature and data to learn Bayesian networks as clinical models of ovarian tumors. - Peter Antal; Geert Fannes; Dirk Timmerman; Yves Moreau; Bart De Moor (Artif. Intell. Medicine, 2004)

Classifying ovarian tumors using Bayesian Multi-Layer Perceptrons and Automatic Relevance Determination: A multi-center study. - Ben Van Calster; Dirk Timmerman; Ian T. Nabney; Lil Valentin; Caroline Van Holsbeke; Sabine Van Huffel (EMBC, 2006)

Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks. - Olivier Gevaert; Frank De Smet; Dirk Timmerman; Yves Moreau; Bart De Moor (ISMB (Supplement of Bioinformatics), 2006)

Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression. - Ben Van Calster; Jan Luts; Johan A. K. Suykens; George Condous; Tom Bourne; Dirk Timmerman; Sabine Van Huffel (ICANN (2), 2007)

Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy. - M. S. Hane Aung; Paulo J. G. Lisboa; Terence A. Etchells; Antonia C. Testa; Ben Van Calster; Sabine Van Huffel; Lil Valentin; Dirk Timmerman (ISNN (2), 2007)

A New Method for Modeling Preoperative Diagnosis of Ovarian Tumors. - Viktoriya Stalbovskaya; Emmanuel C. Ifeachor; Sabine Van Huffel; Dirk Timmerman (IEEE Trans. Biomed. Eng., 2007)

Towards a Clinical Decision Support System for Pregnancies of Unknown Location. - Ben Van Calster; Sabine Van Huffel; Dirk Timmerman; Emma Kirk; Tom Bourne; George Condous (CBMS, 2008)

Multi-class classification of ovarian tumors. - Ben Van Calster; Dirk Timmerman; Antonia C. Testa; Lil Valentin; Sabine Van Huffel (ESANN, 2008)

Multi-class AUC metrics and weighted alternatives. - Ben Van Calster; Vanya Van Belle; George Condous; Tom Bourne; Dirk Timmerman; Sabine Van Huffel (IJCNN, 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)

An application of methods for the probabilistic three-class classification of pregnancies of unknown location. - Ben Van Calster; George Condous; Emma Kirk; Tom Bourne; Dirk Timmerman; Sabine Van Huffel (Artif. Intell. Medicine, 2009)

Clinical decision support for ovarian tumor diagnosis using Bayesian models: Results from the IOTA study. - Ben Van Calster; Olivier Gevaert; Caroline Van Holsbeke; Bart De Moor; Sabine Van Huffel; Dirk Timmerman (Computational Intelligence and Bioengineering, 2009)

Fuzzy Decision Tree Learning for Preoperative Classification of Adnexal Masses. - Emad Ahmadi; Hoda Javadi; Amin Khansefid; Atousa Asadi; Mohammad Mehdi Ebadzadeh; Dirk Timmerman (HEALTHINF, 2011)

Improved modeling of clinical data with kernel methods. - Anneleen Daemen; Dirk Timmerman; Thierry Van den Bosch; Cecilia Bottomley; Emma Kirk; Caroline Van Holsbeke; Lil Valentin; Tom Bourne; Bart De Moor (Artif. Intell. Medicine, 2012)

A spline-based tool to assess and visualize the calibration of multiclass risk predictions. - K. Van Hoorde; Sabine Van Huffel; Dirk Timmerman; Tom Bourne; Ben Van Calster (J. Biomed. Informatics, 2015)

Predictive analytics in health care: how can we know it works? - Ben Van Calster; Laure Wynants; Dirk Timmerman; Ewout W. Steyerberg; Gary S. Collins (J. Am. Medical Informatics Assoc., 2019)

Gradient boosted trees with individual explanations: An alternative to logistic regression for viability prediction in the first trimester of pregnancy. - Thibaut Vaulet; Maya Al-Memar; Hanine Fourie; Shabnam Bobdiwala; Srdjan Saso; Maria Pipi; Catriona Stalder; Phillip R. Bennett; Dirk Timmerman; Tom Bourne; Bart De Moor (Comput. Methods Programs Biomed., 2022)

The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression. - Ruben van den Goorbergh; Maarten van Smeden; Dirk Timmerman; Ben Van Calster (J. Am. Medical Informatics Assoc., 2022)

Understanding random forests and overfitting: a visualization and simulation study. - Lasai Barreñada; Paula Dhiman; Dirk Timmerman; Anne-Laure Boulesteix; Ben Van Calster (CoRR, 2024)

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance. - Ben Van Calster; Gary S. Collins; Andrew J. Vickers; Laure Wynants; Kathleen F. Kerr; Lasai Barreñada; Gaël Varoquaux; Karandeep Singh; Karel G. M. Moons; Tina Hernandez-Boussard; Dirk Timmerman; David J. Mclernon; et al. (CoRR, 2024)