Research Activities

• B-Sreen project: Bayesian networks and computer-aided detection
• TimeBayes and ProBayes projects: Bayesian networks and machine learning
• Protocure project: using formal methods in guideline design
• Theory of model-based diagnosis
• Bayesian network and decision theory
• Logical foundations of knowledge-based systems
• MONET network of excellence (Domain-status report now online)
• ICEA project: Modelling bacterial colonisation by means Bayesian networks, and applying decision theory to improve the use of antibiotics in the intensive care unit (Prototype system)
• NHL and CRC projects: Optimal treatment of patients with cancer (non-Hodgkin lymphoma of the stomach and colorectal cancer)
• Stroke project: Prediction of outcome of stroke, taking MRI data into account
• Vitatron: Intelligent systems for pacemaker reprogramming

Books

• Computer-based Medical Guidelines and Protocols: A Primer and Current Trends. Studies in Health Technology and Informatics, Vol. 139, A. Ten Teije, S. Miksch and P. Lucas, July 2008, approx. 282 pp, hardcover, ISBN: 978-1-58603-873-1
• Advances in Probabilistic Graphical Models. Series: Studies in Fuzziness and Soft Computing , Vol. 213. Lucas, Peter; Gamez, Jose A.; Salmeron, Antonio (Eds.) 2007, X, 396 p., hardcover, ISBN: 978-3-540-68994-2

• Introductory scientific paper about knowledge-based expert systems, written for UNESCO (UNESCO, 2007)

• Conversion of a Rule-based System to a Belief Network (including design issues) (Medical Informatics, 1993)
• Using Theorem Proving Techniques to build Medical Expert Systems (Medical Artificial Intelligence, 1993)
• Refinement of a Rule-based System (Medical Artificial Intelligence, 1994)
• Logic Engineering in Medicine (Knowledge Engineering Review, 1995)
• Knowledge Acquisition for Decision-theoretic Expert Systems (AISB, 1996)
• A Decision-theoretic Network Approach to Treatment Management and Prognosis (Proceedings of ES'97)
• Decision Support in the Management of non-Hodgkin lymphoma of the Stomach (Methods of Information in Medicine, 1998)
• Prognostic methods in medicine (Artificial Intelligence in Medicine, 1999)
• A diagnostic advice systems based on pathophysiological models of diseases (Proceedings MIE99)
• Improving antibiotic therapy of ventilator associated pneumonia using a probabilistic approach (Proceedings MIE99)
• Probabilistic and decision-theoretic approach to the management of infectious disease in the ICU (Artificial Intelligence in Medicine 2000; 19(3): 251-279)
• Prognostic models in medicine: AI and statistical approaches (Methods of Information in Medicine 2001; 40: 1-5)
• Bayesian networks in medicine: a model-based approach to medical decision making (K-P. Adlassnig (ed.), Proceedings of the EUNITE workshop on Intelligent Systems in patient Care, Vienna, Oct. 2001, pp. 73-97)
• A model-based approach to improved prescription of antibiotics (MONET Newsletter, 2003)
• Quality checking of medical guidelines through logical abduction (Proceedings AI-2003, Springer, London, 2003, pp. 309-321)
• Meta-level verification of the quality of medical guidelines using interactive theorem proving (JELIA-2004, LNAI 3229, Springer, Berlin Heidelberg, 2004, pp. 654-666)
• Verification of medical guidelines using background knowledge in task networks (IEEE Transactions on Knowledge and Data Engineering, vol. 19, no. 6, 2007, pp. 832-846)
• Checking the quality of clinical guidelines using automated reasoning tools (Theory and Practice of Logic Programming, vol. 8, pp. 941-641, 2008)
• A decision support system for breast cancer detection in screening program (Proceedings ECAI 2008, pp. 658-662)
• A dynamic Bayesian network for diagnosing ventilator-associated pneumonia in ICU patients (Expert Systems with Applications, vol. 36, 2009, pp. 1249-1258)
• Improved mammographic CAD performance using multi-view information: a Bayesian network framework (Phys. Med. Biol. 54 (2009) 1131-1147)
• Modelling treatment effects in a clinical Bayesian network using Boolean threshold functions (Artificial Intelligence in Medicine, 2009)
• Using model checking for critiquing based on clinical guidelines (Artificial Intelligence in Medicine, vol. 46 (2009) 19-36)
• Causal probabilistic modelling for two-view mammographic analysis (AI in Medicine, LNAI 5651, 2009, pp. 395-404)

Model-based Reasoning and Bayesian Networks

• Symbolic Diagnosis and its Formalisation (Knowledge Engineering Review, 1997)
• Modeling Interactions in Diagnosis (Proceedings of Proceedings of CESA'96 IMACS Multiconference, Symposium on Modelling, Analysis and Simulation, 1996)
• Diagnosis as Hypothesis Refinement (Proceedings of NAIC'97, 1997)
• Analysis of notions of diagnosis (Artificial Intelligence, vol. 105, 1998)
• A model-based system for pacemaker reprogramming (Artificial Intelligence in Medicine 1999; 17: 249-269)
• Certainty-factor-like structures in Bayesian networks (Technical Report, 2000; the Knowledge-based Systems journal 2001; 14: 327-335)
• Bayesian model-based diagnosis (Technical Report, 2000; published in the International Journal of Approximate Reasoning 2001; 27(2): 99-119)
• Comparison of rule-based and Bayesian network approaches in medical diagnostic systems (In: S. Quaglini, P. Barahona, S. Andreassen (eds.). Artificial Intelligence in Medicine (AIME2001), LNAI2101, Springer, Berlin, 2001, pp. 283-292)
• Decision network semantics of branching constraint satisfaction problems (Technical report, NIII-R0209, Institute for Computing and Information Sciences, University of Nijmegen, 2002)
• Bayesian network modelling by qualitative patterns (ECAI 2002, 690-694)
• A system for pacemaker treatment advice (ECAI 2004, pp. 735-739)
• Bayesian network modelling through qualitative patterns (Artificial Intelligence 2005; 163: 233-263)
• Exploiting causal independence in large Bayesian networks (Knowledge-based Systems, 18 (2005) 153-162)
• Conflict-based diagnosis: adding uncertainty to model-based diagnosis (IJCAI 2007, pp. 380-388)
• Explaining clinical decisions by extracting regularity patterns (Decision Support Systems, 44 (2008) 397-408)
• A Bayesian decision-support system for diagnosing ventilator-associated pneumonia (Intensive Care Medicine, 2008)
• Standardizing Research Methods for Prognostics (International Conference on Prognostics and Health Management 2008)
• The Probabilistic Interpretation of Model-based Diagnosis (ECSQARU 2009, LNAI 5590, pp. 204-215)

• Enhancement of learning by declarative expert-based models (IDAMAP, 2000)
• Expert knowledge and its role in learning Bayesian networks in medicine (extended version) (In: S. Quaglini, P. Barahona, S. Andreassen (eds.). Artificial Intelligence in Medicine (AIME2001), LNAI2101, Springer, Berlin, 2001, pp. 156-166)
• Learning Bayesian-network topologies in realistic medical domains (IDAMAP, 2001)
• Restricted Bayesian network structure learning (in: G.A. Gamez, S. Moral, A. Salmeron (eds.). Advances in Bayesian Networks, Studies in Fuzziness and Soft Computing, vol. 146, Springer-Verlag, Berlin, 2004, pp. 217-232). )
• Markov equivalence in Bayesian networks (Technical Report, NIII-R0436, 2004)
• Bayesian analysis, pattern analysis, and data mining in health care (Current Opinion in Critical Care 2004, vol. 10, pp. 399-403)
• Integrating Logical Reasoning and Probabilistic Chain Graphs (Proceedings ECML PKDD 2009, volume 5781 of LNAI, pages 548-563, 2009)

Medicine

• Computer-assisted decision support for the diagnosis and treatment of infectious diseases in intensive care units (The Lancet of Infectious Disease 2005, vol. 5, 305-312)
• Effects of systemic antibiotic therapy on bacterial resistence in the repiratory tract of mechanically ventilated patients (Intensive Care Medicine 2008, vol. 34, pp. 692-699)
• Predicting pathogens causing ventilator-associated pneumonia using a Bayesian network model (Journal of Antimicrobial Chemotherapy 2008, vol. 62, 184-188)

Teaching material

• ACAI09: The Model-based Approach to Medical Decision Support
• Data Mining
• SIKS course Learning and Reasoning:
  Probabilistic Reasoning: Uncertainty and Bayesian Networks
• SIKS course Computational Intelligence:
  Expert Systems: a knowledge-based approach to intelligent systems
• Computational Intelligence
• Programming in Prolog
• Intelligent Systems
• Knowledge Representation and Reasoning
• Medical Informatics