Book (based on my PhD thesis)
Monotone Prediction Models in Data Mining
with H. DanielsVDM Verlag Dr. Müller, ISBN: 978-3639112672, December 2008
Book chapter
- An Advanced Probabilistic Framework for Assisting Screening Mammogram Interpretation
with N. de Carvalho Ferreira, M. Samulski, P. Lucas and N.Karssemeijer
In I. Bichindaritz et al. (Eds.): Computational Intelligence in Healthcare 4, SCI 309, pp. 371-395, Springer, 2010
Journal
- Exploiting causal functional relationships in Bayesian network modelling for personalised healthcare
with J. Terwisscha van Scheltinga, P. Lucas and M. Spaanderman
International Journal of Approximate Reasoning, Forthcoming, 2013 - On the interplay of machine learning and background knowledge in image interpretation by Bayesian networks
with P. Lucas, M. Samulski and N. Karssemeijer
Artificial Intelligence In Medicine, Vol. 57, No 1, pp. 73-86, 2013 - A probabilistic framework for image information fusion with an application to mammographic analysis
with P. Lucas, M. Samulski and N. Karssemeijer
Medical Image Analysis, Vol. 16, No 4, pp. 865-875, 2012 - Monotone and partially monotone neural networks
with H. Daniels
IEEE Transactions on Neural Networks, Vol.21, No 6, pp. 906-917, 2010 - Comparison of universal approximators incorporating partial monotonicity by structure
with A. Minin, B. Lang and H. Daniels
Neural Networks, Vol. 23, No 4, pp. 471-475, 2010 - Improved mammographic CAD performance using multi-view information: A Bayesian network framework
with M. Samulski, P. Lucas and N. Karssemeijer
Physics in Medicine and Biology, Vol. 54, pp. 1131-1147, 2009 - Mixtures of monotone networks for prediction
with H. Daniels and A. Feelders
International Journal of Computational Intelligence, Vol. 3, No 3, pp. 204-214, 2006 - Derivation of monotone decision models from noisy data
with H. Daniels
IEEE Transactions on Systems, Man and Cybernetics, Part C, Vol. 36, No 5, pp. 705-710, 2006 - Decision trees for monotone price models
with H. Daniels
Computational Management Science, Vol. 1, No 3-4, pp. 231-244, 2004
Conference / Workshop
- Inference for a new probabilistic constraint logic
with S. Michels, A. Hommersom, P. Lucas and P. Koopman
23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013 - Probabilistic model-based assessment of information quality in uncertain domains
with S. Michels and P. Lucas
25th Australasian Joint Conference on Artificial Intelligence, LNCS 7691, pp. 890-901, 2012 - Fully-automated interpretation of biochemical tests for decision support by smartphones
with P. Lucas, R. Smeets and J. Terwisscha van Scheltinga
25th IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2012 - A predictive Bayesian network model for home management of preeclampsia
with P. Lucas and M. Spaanderman
13th Conference on Artificial Intelligence in Medicine (AIME), LNAI 6747, pp. 179-183, 2011 - e-MomCare: a personalised home-monitoring system for pregnancy disorders
with P. Lucas and M. Spaanderman
5th International Workshop on Personalisation for e-Health (Pers4eHealth), LNICST 69, pp. 267-274, 2011 - Discretisation does affect the performance of Bayesian networks
with S. Robben, P. Lucas and M. Samulski
30th SGAI International Conference on Artificial Intelligence, Research and Development in Intelligent Systems XXVII, pp. 237-250, 2011 - Critiquing Knowledge Representation in Medical Image Interpretation using Structure Learning
with N. Radstake, P. Lucas and M. Samulski
2nd Workshop "Knowledge Representation for Health Care" (KR4HC), LNAI 6512, pp. 56-69, 2011 - Using Local Context Information to Improve Automatic Mammographic Mass Detection
with P. Lucas and N. Karssemeijer
13th World Congress on Medical and Health Informatics (MEDINFO), Vol. 160 (Pt 2), pp. 1291-1295, 2010 - Improved mammographic CAD performance using multi-view information: A Bayesian network framework
with M. Samulski, P. Lucas and N. Karssemeijer
21st Benelux Conference on Artificial Intelligence (BNAIC), Compressed contribution, pp. 379-381, 2009 - Causal probabilistic modelling for two-view mammographic analysis
with M. Samulski, P. Lucas and N. Karssemeijer
12th Conference on Artificial Intelligence in Medicine (AIME), LNAI 5651, pp. 395-404, 2009 - On testing monotonicity of datasets
with H. Daniels
ECML/PKDD Workshop "Learning Monotone Models From Data", pp.11-23, 2009 - Toward expert knowledge representation for automatic breast cancer detection
with M. Samulski, N. Karssemeijer and P. Lucas
13th biennial International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), LNAI 5253, pp. 333-344, 2008 - Partially monotone networks applied to breast cancer detection on mammograms
with H. Daniels and M. Samulski
18th International Conference on Artificial Neural Networks (ICANN), LNCS 5163, pp. 917-926, 2008 - A decision support system for breast cancer detection in screening programs
with P. Lucas, N. de Carvalho Ferreira, M. Samulski and N.Karssemeijer
18th biennial European Conference on Artificial Intelligence (ECAI), Vol. 178, pp. 658-662, 2008 - Bayesian network decomposition for modeling breast cancer detection
with N. de Carvalho Ferreira and P. Lucas
11th Conference on Artificial Intelligence in Medicine (AIME) 2007, LNAI 4594, pp. 346-350, 2007 - Solving partially monotone problems with neural networks
with H. Daniels and A.Feelders
12th International Conference on Computer Science, Vol. 12, pp. 82-87, March 29-31, 2006
Reviewed paper
- Bayesian Modelling of Multi-View Mammography
with N. de Carvalho Ferreira and P. Lucas
Presented at the ICML workshop "Machine Learning for Health Care Applications", 2008 - Enforcing Monotonicity of Decision Models: Algorithm and Performance, A Case Study of Hedonic Price Model
with H. Daniels
Presented at the 9th International Conference of Computing in Economics and Finance, 2003
Technical report
- A probabilistic logic-based model for fusing attribute information of objects under surveillance
with S. Michels, A.J. Hommersom and P.J.F. Lucas
Radboud University Nijmegen, Technical report: ICIS-R12006, 2012 - Two polynomial algorithms for relabeling non-monotone data
with A. Feelders and H. Daniels
Utrecht University, Technical Report: UU-CS-2006-046, 2006 - Derivation of monotone decision models from non-monotone data
with H. Daniels
Tilburg University, Center Internal Report: 2003-30, 2003