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

Patrick Benedict Hans Juan Grossmann

Research output: ThesisDoctoral ThesisExternal prepared

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Abstract

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
Supervisors/Advisors
  • Lambin, Philippe, Supervisor
  • Aerts, H., Advisor, External person
Award date8 Mar 2018
Place of PublicationMaastricht
Publisher
Print ISBNs9789461598103
DOIs
Publication statusPublished - 2018

Keywords

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

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