Computational methods for survival analysis

  • Vehtari, Aki (Principal investigator)
  • Andersen, Michael (Project Member)
  • Siivola, Eero (Project Member)
  • Magnusson, Måns (Project Member)
  • Paananen, Topi (Project Member)
  • Säilynoja, Teemu (Project Member)
  • Dhaka, Akash (Project Member)
  • Sivula, Tuomas (Project Member)

Project Details


The objective of the proposed research is to develop novel computational methods for the statistical analysis of survival data, with particular focus on CVD and diabetes diagnostics, and cancer treatment and follow-up. The developed survival analysis methods will provide better predictive performance than the currently used methods, which will increase understanding about the analysed data sets. Improvements in predictive performance can lead to significant improvements in targeting treatments and thus globally reduce suffering of the patients and the cost of treatments, preventive therapies and follow-up methods. We expect that the results from the research project will lead to changes in internationally accepted recommendations for cancer treatments and cardiovascular disease (CVD) risk predictions.
Effective start/end date01/09/201631/08/2020

Collaborative partners


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