About Me
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
Engineering & Materials Science
# Bayesian Networks
# Hidden Markov Models
# Unsupervised Learning
Medicine & Life Sciences
# Chronic Obstructive Pulmonary Disease
# Randomized Controlled Trials
# Self-Management
# Telemedicine
# Validation Studies
Organisations
Research
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
Recent
Dal, G. (2024).
Probabilistic Inference Using Partitioned Bayesian Networks: Introducing a Compositional Framework. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente.
https://doi.org/10.3990/1.9789036559744
Zanga, A., Bernasconi, A.
, Lucas, P. J. F., Pijnenborg, H., Reijnen, C., Scutari, M., & Stella, F. (2023).
Causal Discovery with Missing Data in a Multicentric Clinical Study. In J. M. Juarez, M. Marcos, G. Stiglic, & A. Tucker (Eds.),
Artificial Intelligence in Medicine: 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12–15, 2023, Proceedings (pp. 40-44). (Lecture Notes in Computer Science; Vol. 13897). Springer.
https://doi.org/10.1007/978-3-031-34344-5_5
Bernasconi, A., Zanga, A.
, Lucas, P. J. F., Scutari, M., & Stella, F. (2023).
Towards a Transportable Causal Network Model Based on Observational Healthcare Data. In F. Calimeri , M. Dragoni , & F. Stella (Eds.),
HC@AIxIA 2023: Proceedings of the 2nd AIxIA Workshop on Artificial Intelligence For Healthcare (HC@AIxIA 2023) (pp. 122-129). (CEUR workshop proceedings; Vol. 3578). CEUR.
https://ceur-ws.org/Vol-3578/paper7.pdf
Dal, G. H.
, Laarman, A.
, & Lucas, P. J. F. (2023).
ParaGnosis: A Tool for Parallel Knowledge Compilation. In G. Caltais, & C. Schilling (Eds.),
Model Checking Software: 29th International Symposium, SPIN 2023, Paris, France, April 26–27, 2023, Proceedings (pp. 22-37). (Lecture Notes in Computer Science; Vol. 13872). Springer.
https://doi.org/10.1007/978-3-031-32157-3_2
Apriyanti, D. H.
, Spreeuwers, L. J.
, & Lucas, P. J. F. (2023).
Deep neural networks for explainable feature extraction in orchid identification.
Applied intelligence,
53(21), 26270-26285.
https://doi.org/10.1007/s10489-023-04880-2
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. (2023).
Improved preoperative risk stratification in endometrial carcinoma patients: external validation of the ENDORISK Bayesian network model in a large population-based case series.
Journal of Cancer Research and Clinical Oncology,
149, 3361–3369.
https://doi.org/10.1007/s00432-022-04218-4
Muller-Sielaff, J., Beladi, S. B., Meuschke, M., Vrede, S.
, Lucas, P. J. F., Pijnenborg, J. M. A., & Oeltze-Jafra, S. (2023).
Visual Assistance in Development and Validation of Bayesian Networks for Clinical Decision Support.
IEEE transactions on visualization and computer graphics,
29(8), 3602-3616.
https://doi.org/10.1109/TVCG.2022.3166071
Zanga, A., Bernasconi, A.
, Lucas, P. J. F., Pijnenborg, H., Reijnen, C., Scutari, M., & Stella, F. (2022).
Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal Approach. In F. Calimeri, M. Dragoni, & F. Stella (Eds.),
HC@AIxIA 2022: 1st AIxIA Workshop on Artificial Intelligence For Healthcare (HC@AIxIA 2022) (pp. 1-15). (CEUR workshop proceedings; Vol. 3307). CEUR.
https://ceur-ws.org/Vol-3307/paper1.pdf
Vinklerová, P., Ovesná, P., Hausnerová, J., Pijnenborg, J. M. A.
, Lucas, P. J. F., Reijnen, C., Vrede, S., & Weinberger, V. (2022).
External validation study of endometrial cancer preoperative risk stratification model (ENDORISK).
Frontiers in oncology,
12, Article 939226.
https://doi.org/10.3389/fonc.2022.939226
Kleinau, A., Mo, A., Stella, F. A., Müller-Sielaff, J., Pijnenborg, J. M. A.
, Lucas, P. J. F., & Oeltze-Jafra, S. (2021).
User-centered Development of a Clinical Decision Support System. In
SMARTERCARE 2021: Towards Smarter Health Care: Can Artificial Intelligence Help? (pp. 67-78). (CEUR workshop proceedings; Vol. 3060). CEUR.
https://ceur-ws.org/Vol-3060/paper-8.pdf
UT Research Information System
Google Scholar Link
Education
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
Contact Details
Visiting Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(building no. 11), room 4074
Hallenweg 19
7522NH Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
4074
P.O. Box 217
7500 AE Enschede
The Netherlands