Topics of Interest

  • Probabilistic modelling methods applied to biomedical problems:
    • Probabilistic graphical models (such as, Bayesian networks, Markov models, causal networks, etc.)
    • Dynamic probabilistic models (MDPs, POMDPs, DBNs, ...)
    • Influence diagrams and decision networks
    • Probabilistic logics
    • Imprecise probabilities
  • Innovative probabilistic methods for biomedical problem solving:
    • Diagnostic models
    • Prediction models for prognosis
    • Treatment selection and monitoring
    • Multi-morbidity models
    • Epidemiological models, e.g., of infectious disease spread
  • Learning methods:
    • Multi-relational learning
    • Probabilistic structure and parameter learning
    • Probabilistic classifiers
  • Innovative biomedical applications of probabilistic models:
    • Probabilistic models for personalised medicine
    • Patient (tele)medicine (in the management of stroke, COPD, diabetes, etc.)
    • Probabilistic models for translational medicine
    • Analysis of clinical practice guidelines
  • Evaluation of probabilistic biomedical models in practice