Defining the biological and clinical basis of radiomics: towards clinical imaging biomarkers

Patrick Benedict Hans Juan Grossmann

Research output: ThesisDoctoral ThesisExternal prepared

4129 Downloads (Pure)


Artificial Intelligence is on the verge of gaining a seminal role in advanced medicine. This brings new hope for modern cancer care, where success of treatment often depends on identifying targeted therapies that match a patient’s disease profile. In this dissertation, for the first time radiographic, biological, and clinical data were integrated to develop intelligent models that can predict which patients will respond better to a specific therapy. Based on the results of this dissertation, in the future doctors could use the proposed machine learning approach to analyse patients in a way that allows selection of optimal treatment strategies.
Original languageEnglish
Awarding Institution
  • Maastricht University
  • Lambin, Philippe, Supervisor
  • Aerts, H., Co-Supervisor, External person
Award date8 Mar 2018
Place of PublicationMaastricht
Print ISBNs9789461598103
Publication statusPublished - 2018


  • AI
  • cancer
  • precision medicine
  • big data
  • machine learning
  • radiomics
  • genomics
  • diagnostic
  • survival

Cite this