Guest staff

prof.dr. P.J.F. Lucas MD (Peter)

Professor Emeritus
EEMCS-CS-DMB
Zilverling 4074
p.j.f.lucas@utwente.nl
+31534899297
Business card

Peter Lucas currently works at the Data Science Department, EEMCS Faculty of the University of Twente. Until the end of 2018 he worked also at the Institute for Computing and Information Sciences at Radboud University Nijmegen, where he still can be found occasionally as a guest.

Expertise

  • Computer Science

    • Bayesian Networks
    • Models
    • Probability
    • User

  • Medicine and Dentistry

    • Patient
    • Endometrial Cancer
    • Disease
    • Risk Stratification

Organisations

More than 35 years of experience as an AI researcher in areas such as intelligent systems, computer-based reasoning, decision support systems, model-based reasoning and diagnosis, Bayesian networks, machine learning, eHealth. At the moment most of my research is on probabilistic graphical models, statistical machine learning, and clinical statistical model building. I also have an interest in model-based reasoning and probabilistic logic also applied to other areas than medicine.

Publications

2024
Probabilistic Inference Using Partitioned Bayesian Networks: Introducing a Compositional Framework. University of Twente. Dal, G.https://doi.org/10.3990/1.9789036559744
2023
Deep neural networks for explainable feature extraction in orchid identification, 26270-26285. Apriyanti, D. H., Spreeuwers, L. J. & Lucas, P. J. F.https://doi.org/10.1007/s10489-023-04880-2Visual Assistance in Development and Validation of Bayesian Networks for Clinical Decision Support, 3602-3616. Muller-Sielaff, J., Beladi, S. B., Meuschke, M., Vrede, S., Lucas, P. J. F., Pijnenborg, J. M. A. & Oeltze-Jafra, S.https://doi.org/10.1109/TVCG.2022.3166071Improved preoperative risk stratification in endometrial carcinoma patients: external validation of the ENDORISK Bayesian network model in a large population-based case series, 3361–3369. Grube, M., Reijnen, C., Lucas, P. J. F., Kommoss, F., Kommoss, F. K. F., Brucker, S. Y., Walter, C. B., Oberlechner, E., Krämer, B., Andress, J., Neis, F., Staebler, A., Pijnenborg, J. M. A. & Kommoss, S.https://doi.org/10.1007/s00432-022-04218-4ParaGnosis: A Tool for Parallel Knowledge CompilationIn Model Checking Software: 29th International Symposium, SPIN 2023, Paris, France, April 26–27, 2023, Proceedings (pp. 22-37). Springer. Dal, G. H., Laarman, A. & Lucas, P. J. F.https://doi.org/10.1007/978-3-031-32157-3_2Towards a Transportable Causal Network Model Based on Observational Healthcare DataIn HC@AIxIA 2023: Proceedings of the 2nd AIxIA Workshop on Artificial Intelligence For Healthcare (HC@AIxIA 2023) (pp. 122-129). CEUR. Bernasconi, A., Zanga, A., Lucas, P. J. F., Scutari, M. & Stella, F.https://ceur-ws.org/Vol-3578/paper7.pdfCausal Discovery with Missing Data in a Multicentric Clinical StudyIn Artificial Intelligence in Medicine: 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12–15, 2023, Proceedings (pp. 40-44). Springer. Zanga, A., Bernasconi, A., Lucas, P. J. F., Pijnenborg, H., Reijnen, C., Scutari, M. & Stella, F.https://doi.org/10.1007/978-3-031-34344-5_5
2022
External validation study of endometrial cancer preoperative risk stratification model (ENDORISK), Article 939226. Vinklerová, P., Ovesná, P., Hausnerová, J., Pijnenborg, J. M. A., Lucas, P. J. F., Reijnen, C., Vrede, S. & Weinberger, V.https://doi.org/10.3389/fonc.2022.939226Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal ApproachIn HC@AIxIA 2022: 1st AIxIA Workshop on Artificial Intelligence For Healthcare (HC@AIxIA 2022) (pp. 1-15). CEUR. Zanga, A., Bernasconi, A., Lucas, P. J. F., Pijnenborg, H., Reijnen, C., Scutari, M. & Stella, F.https://ceur-ws.org/Vol-3307/paper1.pdf
2021
A compositional approach to probabilistic knowledge compilation, 38-66. Dal, G. H., Laarman, A. W., Hommersom, A. & Lucas, P. J. F.https://doi.org/10.1016/j.ijar.2021.07.007

Research profiles

Involved in supervision of students with an interest in AI, and in particular Bayesian networks and knowledge representation an reasoning.

Courses academic year 2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2022/2023

Address

University of Twente

Zilverling (building no. 11), room 4074
Hallenweg 19
7522 NH Enschede
Netherlands

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Organisations

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