Prescription data and demographics: An explainable machine learning exploration of colorectal cancer risk factors based on data from Danish national registries.

Journal: Computer methods and programs in biomedicine
Published Date: Apr 24, 2025

Abstract

OBJECTIVES: Despite substantial advancements in both treatment and prevention, colorectal cancer continues to be a leading cause of global morbidity and mortality. This study investigated the potential of using demographics and prescribed drug information to predict risk of colorectal cancer using a machine learning approach.

Authors

  • Abdolrahman Peimankar
    SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense 5230, Denmark. Electronic address: abpe@mmmi.sdu.dk.
  • Olav Sivertsen Garvik
    Center for Clinical Epidemiology, Odense University Hospital, 5230 Odense, Denmark; Research Unit of Clinical Epidemiology, University of Southern Denmark, 5230 Odense, Denmark.
  • Bente Mertz Nørgård
    Center for Clinical Epidemiology, Odense University Hospital, 5230 Odense, Denmark; Research Unit of Clinical Epidemiology, University of Southern Denmark, 5230 Odense, Denmark.
  • Jens Søndergaard
    Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5230 Odense, Denmark.
  • Dorte Ejg Jarbøl
    Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5230 Odense, Denmark.
  • Sonja Wehberg
    Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5230 Odense, Denmark.
  • Søren Paludan Sheikh
    Center for Regenerative Medication, Odense University Hospital, 5230 Odense, Denmark.
  • Ali Ebrahimi
    Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD.
  • Uffe Kock Wiil
    Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Denmark.
  • Maria Iachina
    Center for Clinical Epidemiology, Odense University Hospital, 5230 Odense, Denmark; Research Unit of Clinical Epidemiology, University of Southern Denmark, 5230 Odense, Denmark.

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