90-day mortality prediction in elective visceral surgery using machine learning: a retrospective multicenter development, validation, and comparison study.

Journal: International journal of surgery (London, England)
Published Date: Apr 1, 2025

Abstract

BACKGROUND: Machine Learning (ML) is increasingly being adopted in biomedical research, however, its potential for outcome prediction in visceral surgery remains uncertain. This study compares the potential of ML methods for preoperative 90-day mortality (90DM) prediction of an aggregated multi-organ approach to conventional scoring systems and individual organ models.

Authors

  • Christoph Riepe
    Charité- Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Surgery, Berlin, Germany.
  • Robin van de Water
    Hasso Plattner Institute (HPI), Universität Potsdam, Digital Health Cluster, Potsdam, Germany.
  • Axel Winter
  • Bjarne Pfitzner
  • Lara Faraj
    Einstein Center for Neurosciences (ECN), Charité- Universitätsmedizin Berlin, Berlin, Germany.
  • Robert Ahlborn
    Charité- Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Informatics, Berlin, Germany.
  • Maximilian Schulze
    Charité- Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Surgery, Berlin, Germany.
  • Daniela Zuluaga
    Charité- Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Surgery, Berlin, Germany.
  • Christian Schineis
    Charité- Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of General and Abdominal Surgery, Berlin, Germany.
  • Katharina Beyer
    Department of General and Visceral Surgery, Charité-Universitätsmedizin Berlin, Berlin, Germany.
  • Johann Pratschke
    Charite University Medicine Berlin, Berlin, Germany.
  • Bert Arnrich
    Hasso Plattner Institute, University of Potsdam, Germany.
  • Igor M Sauer
  • Max M Maurer

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