An Ontological Model for Analyzing Liver Cancer Medical Reports

  • Rim MessaoudiEmail author
  • Taher Labidi
  • Antoine Vacavant
  • Faiez Gargouri
  • Manuel Grand-Brochier
  • Ali Amouri
  • Hela Fourati
  • Achraf Mtibaa
  • Faouzi Jaziri
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 341)


The rapid adoption of Electronic Health Record (EHR) systems requires advanced enactment strategies for analyzing medical reports. Indeed, the information presented in these reports is difficult to access and it is onerous to analyze it by medical decision support systems. Medical reports characterize full descriptions of the patient diagnosis process. They bring together information about exam steps such as applied techniques, results, synthesis and medical conclusions. In this paper, we propose a medical report modeling and analyzing approach that aims to analyze medical reports for Magnetic Resonance Imaging (MRI) exams. Ontological model is dedicated to represent information from radiological reports in order to make them comprehensible and machine readable. Moreover, reasoning techniques are used to treat a large amount of clinical data. This provides an analyzing system allowing user to be informed about the evolution of the patient state. The proposed system was successfully applied to a set of Hepatocellular Carcinoma (HCC) medical reports from University Hospital of Clermont-Ferrand (CHU), France.


Ontology MRI reports Liver cancer Reasoning rules 



This work was financially supported by the “PHC Utique” program of the French Ministry of Foreign A airs and Ministry of higher education and research and the Tunisian Ministry of higher education and scientific research in the CMCU project number 18G139.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rim Messaoudi
    • 1
    • 2
    Email author
  • Taher Labidi
    • 1
    • 4
  • Antoine Vacavant
    • 3
  • Faiez Gargouri
    • 1
    • 6
  • Manuel Grand-Brochier
    • 3
  • Ali Amouri
    • 5
  • Hela Fourati
    • 5
  • Achraf Mtibaa
    • 1
    • 4
  • Faouzi Jaziri
    • 3
  1. 1.MIRACL LaboratoryUniversity of SfaxSfaxTunisia
  2. 2.CRNS LaboratoryUniversity of SfaxSfaxTunisia
  3. 3.Institut PascalUniversité Clermont AuvergneClermont-FerrandFrance
  4. 4.National School of Electronic and TelecommunicationsUniversity of SfaxSfaxTunisia
  5. 5.CHU Hédi ChakerSfaxTunisia
  6. 6.Higher Institute of Computer Science and MultimediaUniversity of SfaxSfaxTunisia

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