| Monotone and partially monotone neural networks H Daniels, M Velikova IEEE Transactions on Neural Networks 21 (6), 906-917, 2010 | 229 | 2010 |
| Exploiting causal functional relationships in Bayesian network modelling for personalised healthcare M Velikova, JT Van Scheltinga, PJF Lucas, M Spaanderman International Journal of Approximate Reasoning 55 (1), 59-73, 2014 | 106 | 2014 |
| Learning Bayesian networks for clinical time series analysis M Van der Heijden, M Velikova, PJF Lucas Journal of biomedical informatics 48, 94-105, 2014 | 75 | 2014 |
| Improved mammographic CAD performance using multi-view information: a Bayesian network framework M Velikova, M Samulski, PJF Lucas, N Karssemeijer Physics in Medicine & Biology 54 (5), 1131, 2009 | 74 | 2009 |
| On the interplay of machine learning and background knowledge in image interpretation by Bayesian networks M Velikova, PJF Lucas, M Samulski, N Karssemeijer Artificial intelligence in medicine 57 (1), 73-86, 2013 | 54 | 2013 |
| Derivation of monotone decision models from noisy data HAM Daniels, MV Velikova IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2006 | 48 | 2006 |
| MoSHCA-my mobile and smart health care assistant A Hommersom, PJF Lucas, M Velikova, G Dal, J Bastos, J Rodriguez, ... 2013 IEEE 15th International Conference on e-Health Networking, Applications …, 2013 | 47 | 2013 |
| A probabilistic framework for image information fusion with an application to mammographic analysis M Velikova, PJF Lucas, M Samulski, N Karssemeijer Medical Image Analysis 16 (4), 865-875, 2012 | 40 | 2012 |
| Comparison of universal approximators incorporating partial monotonicity by structure A Minin, M Velikova, B Lang, H Daniels Neural Networks 23 (4), 471-475, 2010 | 38 | 2010 |
| A digital twin method for automated behavior analysis of large-scale distributed IoT systems J Sleuters, Y Li, J Verriet, M Velikova, R Doornbos 2019 14th Annual Conference System of Systems Engineering (SoSE), 7-12, 2019 | 33 | 2019 |
| Derivation of monotone decision models from non-monotone data HAM Daniels, MV Velikova | 25 | 2003 |
| Decision trees for monotone price models M Velikova, H Daniels Computational Management Science 1, 231-244, 2004 | 24 | 2004 |
| A new probabilistic constraint logic programming language based on a generalised distribution semantics S Michels, A Hommersom, PJF Lucas, M Velikova Artificial Intelligence 228, 1-44, 2015 | 22 | 2015 |
| An integrated reconfigurable system for maritime situational awareness M Velikova, P Novák, B Huijbrechts, J Laarhuis, J Hoeksma, S Michels ECAI 2014, 1197-1202, 2014 | 19 | 2014 |
| Smartphone‐based analysis of biochemical tests for health monitoring support at home M Velikova, RL Smeets, JT van Scheltinga, PJF Lucas, M Spaanderman Healthcare technology letters 1 (3), 92-97, 2014 | 18 | 2014 |
| A decision support system for breast cancer detection in screening programs M Velikova, PJF Lucas, N Ferreira, M Samulski, N Karssemeijer ECAI 2008, 658-662, 2008 | 16 | 2008 |
| Solving partially monotone problems with neural networks M Velikova, H Daniels, A Feelders Proceedings of the International Conference on Neural Networks, Vienna, Austria, 2006 | 16 | 2006 |
| Intelligent disease self-management with mobile technology M Velikova, PJF Lucas, M van der Heijden Computer 48 (2), 32-39, 2015 | 14 | 2015 |
| A decision support model for uncertainty reasoning in safety and security tasks S Michels, M Velikova, A Hommersom, PJF Lucas 2013 IEEE International Conference on Systems, Man, and Cybernetics, 663-668, 2013 | 14 | 2013 |
| Fully-automated interpretation of biochemical tests for decision support by smartphones M Velikova, PJF Lucas, RL Smeets, JT van Scheltinga 2012 25th IEEE International Symposium on Computer-Based Medical Systems …, 2012 | 14 | 2012 |
