| Exploiting experts’ knowledge for structure learning of Bayesian networks H Amirkhani, M Rahmati, PJF Lucas, A Hommersom IEEE transactions on pattern analysis and machine intelligence 39 (11), 2154 …, 2016 | 83 | 2016 |
| Discovering software vulnerabilities using data-flow analysis and machine learning J Kronjee, A Hommersom, H Vranken Proceedings of the 13th international conference on availability …, 2018 | 70 | 2018 |
| Multilevel temporal Bayesian networks can model longitudinal change in multimorbidity M Lappenschaar, A Hommersom, PJF Lucas, J Lagro, S Visscher, ... Journal of clinical epidemiology 66 (12), 1405-1416, 2013 | 67 | 2013 |
| Multilevel Bayesian networks for the analysis of hierarchical health care data M Lappenschaar, A Hommersom, PJF Lucas, J Lagro, S Visscher Artificial intelligence in medicine 57 (3), 171-183, 2013 | 57 | 2013 |
| 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 |
| Verification of medical guidelines using background knowledge in task networks A Hommersom, P Groot, PJF Lucas, M Balser, J Schmitt IEEE Transactions on Knowledge and Data Engineering 19 (6), 832-846, 2007 | 43 | 2007 |
| Using model checking for critiquing based on clinical guidelines P Groot, A Hommersom, PJF Lucas, RJ Merk, A ten Teije, F van Harmelen, ... Artificial Intelligence in Medicine 46 (1), 19-36, 2009 | 39 | 2009 |
| Checking the quality of clinical guidelines using automated reasoning tools A Hommersom, PJF Lucas, P Van Bommel Theory and Practice of Logic Programming 8 (5-6), 611-641, 2008 | 39* | 2008 |
| A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity M Liu, F Stella, A Hommersom, PJF Lucas, L Boer, E Bischoff Artificial intelligence in medicine 95, 104-117, 2019 | 37 | 2019 |
| Update semantics of security protocols A Hommersom, JJ Meyer, E De Vink Information, interaction and agency, 289-327, 2005 | 35* | 2005 |
| Denial-of-service attacks on LoRaWAN E Van Es, H Vranken, A Hommersom Proceedings of the 13th International Conference on Availability …, 2018 | 33 | 2018 |
| Adaptation of clinical practice guidelines P Groot, A Hommersom, P Lucas Computer-based Medical Guidelines and Protocols: A Primer and Current Trends …, 2008 | 32 | 2008 |
| 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 | 30* | 2015 |
| Understanding disease processes by partitioned dynamic Bayesian networks MLP Bueno, A Hommersom, PJF Lucas, M Lappenschaar, JGE Janzing Journal of biomedical informatics 61, 283-297, 2016 | 29 | 2016 |
| Probabilistic causal models of multimorbidity concepts M Lappenschaar, A Hommersom, PJF Lucas AMIA Annual Symposium Proceedings 2012, 475, 2012 | 29 | 2012 |
| Using Bayesian networks in an industrial setting: Making printing systems adaptive A Hommersom, PJF Lucas ECAI 2010, 401-406, 2010 | 20* | 2010 |
| Meta-level verification of the quality of medical guidelines using interactive theorem proving A Hommersom, P Lucas, M Balser European Workshop on Logics in Artificial Intelligence, 654-666, 2004 | 20 | 2004 |
| Asymmetric hidden Markov models MLP Bueno, A Hommersom, PJF Lucas, A Linard International Journal of Approximate Reasoning 88, 169-191, 2017 | 19 | 2017 |
| Hybrid time Bayesian networks M Liu, A Hommersom, M van der Heijden, PJF Lucas International Journal of Approximate Reasoning 80, 460-474, 2017 | 19 | 2017 |
| The role of model checking in critiquing based on clinical guidelines P Groot, A Hommersom, P Lucas, R Serban, A Ten Teije, F Van Harmelen Artificial Intelligence in Medicine: 11th Conference on Artificial …, 2007 | 19* | 2007 |
Peter LucasThe Bayesian Institute; University of Twente; guest at Radboud UniversityEmail verificata su cs.ru.nl
