From data to decision: a knowledge engineering approach to individualise cancer therapy

Hendrik A. Roelofs

Research output: ThesisDoctoral ThesisExternal prepared

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Abstract

Immensely powerful knowledge is hidden in the vast amounts of information we produce daily. Not only from our public’s socio-economic behaviour and health status, which we increasingly share online, but also from the treatment data we generate and collect in our clinical routine. What if we could harvest and exploit this wealth to enable the right treatment for the right patient?
This thesis discusses several Rapid Learning components that are needed to provide decision support systems, which help to determine the optimal therapy for cancer patients, taking cost-effectiveness into account. By incorporating cost-effectiveness analyses, even proton therapy is an option.
Original languageEnglish
Awarding Institution
  • Maastricht University
Supervisors/Advisors
  • Lambin, Philippe, Supervisor
  • Dekker, Andre, Supervisor
Award date8 Jul 2016
Publication statusPublished - 2016

Keywords

  • data
  • Rapid Learning
  • cancer therapy

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