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Dirk Timmerman
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2020 – today
- 2024
- [i1]Lasai Barreñada, Paula Dhiman, Dirk Timmerman, Anne-Laure Boulesteix, Ben Van Calster:
Understanding random forests and overfitting: a visualization and simulation study. CoRR abs/2402.18612 (2024) - 2022
- [j11]Thibaut Vaulet
, Maya Al-Memar, Hanine Fourie
Gradient boosted trees with individual explanations: An alternative to logistic regression for viability prediction in the first trimester of pregnancy. Comput. Methods Programs Biomed. 213: 106520 (2022) - [j10]Ruben van den Goorbergh, Maarten van Smeden
The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression. J. Am. Medical Informatics Assoc. 29(9): 1525-1534 (2022)
2010 – 2019
- 2019
- [j9]Ben Van Calster
Predictive analytics in health care: how can we know it works? J. Am. Medical Informatics Assoc. 26(12): 1651-1654 (2019) - 2015
- [j8]K. Van Hoorde, Sabine Van Huffel, Dirk Timmerman
A spline-based tool to assess and visualize the calibration of multiclass risk predictions. J. Biomed. Informatics 54: 283-293 (2015) - 2012
- [j7]Anneleen Daemen, Dirk Timmerman
Improved modeling of clinical data with kernel methods. Artif. Intell. Medicine 54(2): 103-114 (2012) - 2011
- [c14]Emad Ahmadi, Hoda Javadi, Amin Khansefid, Atousa Asadi, Mohammad Mehdi Ebadzadeh, Dirk Timmerman:
Fuzzy Decision Tree Learning for Preoperative Classification of Adnexal Masses. HEALTHINF 2011: 364-375
2000 – 2009
- 2009
- [j6]Ben Van Calster
An application of methods for the probabilistic three-class classification of pregnancies of unknown location. Artif. Intell. Medicine 46(2): 139-154 (2009) - [p1]Ben Van Calster, Olivier Gevaert
Clinical decision support for ovarian tumor diagnosis using Bayesian models: Results from the IOTA study. Computational Intelligence and Bioengineering 2009: 111-128 - 2008
- [j5]Ben Van Calster, Dirk Timmerman
Using Bayesian neural networks with ARD input selection to detect malignant ovarian masses prior to surgery. Neural Comput. Appl. 17(5-6): 489-500 (2008) - [c13]Ben Van Calster, Sabine Van Huffel, Dirk Timmerman
Towards a Clinical Decision Support System for Pregnancies of Unknown Location. CBMS 2008: 581-583 - [c12]Ben Van Calster, Dirk Timmerman, Antonia C. Testa, Lil Valentin, Sabine Van Huffel:
Multi-class classification of ovarian tumors. ESANN 2008: 65-70 - [c11]Ben Van Calster, Vanya Van Belle, George Condous, Tom Bourne
Multi-class AUC metrics and weighted alternatives. IJCNN 2008: 1390-1396 - 2007
- [j4]Viktoriya Stalbovskaya, Emmanuel C. Ifeachor, Sabine Van Huffel, Dirk Timmerman
A New Method for Modeling Preoperative Diagnosis of Ovarian Tumors. IEEE Trans. Biomed. Eng. 54(11): 2064-2072 (2007) - [c10]Ben Van Calster, Jan Luts, Johan A. K. Suykens, George Condous, Tom Bourne, Dirk Timmerman
Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression. ICANN (2) 2007: 139-148 - [c9]M. S. Hane Aung, Paulo J. G. Lisboa, Terence A. Etchells, Antonia C. Testa
Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy. ISNN (2) 2007: 1177-1186 - 2006
- [c8]Ben Van Calster
Classifying ovarian tumors using Bayesian Multi-Layer Perceptrons and Automatic Relevance Determination: A multi-center study. EMBC 2006: 5342-5345 - [c7]Olivier Gevaert
Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks. ISMB (Supplement of Bioinformatics) 2006: 184-190 - 2004
- [j3]Peter Antal
Using literature and data to learn Bayesian networks as clinical models of ovarian tumors. Artif. Intell. Medicine 30(3): 257-281 (2004) - 2003
- [j2]Chuan Lu
Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines. Artif. Intell. Medicine 28(3): 281-306 (2003) - [j1]Peter Antal
Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor classification with rejection. Artif. Intell. Medicine 29(1-2): 39-60 (2003) - [c6]Chuan Lu
Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines. AIME 2003: 219-228 - 2002
- [c5]Peter Antal, Dirk Timmerman
Domain Knowledge Based Information Retrieval Language: An Application Of Annotated Bayesian Network In Ovarian Cancer Domain. CBMS 2002: 213-218 - [c4]Stein Aerts
Web-based Data Collection for Uterine Adnexal Tumors: A Case Study. CBMS 2002: 282-287 - 2001
- [c3]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
- [c2]Peter Antal, Herman Verrelst, Dirk Timmerman
Bayesian Networks in Ovarian Cancer Diagnosis: Potentials and Limitations. CBMS 2000: 103-108
1990 – 1999
- 1997
- [c1]Herman Verrelst, Yves Moreau, Joos Vandewalle, Dirk Timmerman:
Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors. NIPS 1997: 978-984
Coauthor Index
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last updated on 2024-06-10 21:22 CEST by the dblp team
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