Improving a data mining based diagnostic support tool for rare diseases on the example of M. Fabry: Gender differences need to be taken into account.

Journal: PloS one
Published Date: Jun 30, 2025

Abstract

BACKGROUND: Rare diseases often present with a variety of clinical symptoms and therefore are challenging to diagnose. Fabry disease is an x-linked rare metabolic disorder. The severity of symptoms is usually different in men and women. Since therapeutic options for Fabry disease exist, early diagnosis is important. An artificial intelligence (AI)-based diagnosis support algorithm for rare diseases has been developed in preliminary studies.

Authors

  • Philipp Hahn
    University Children's Hospital, Ruhr-University Bochum, Bochum, Germany.
  • Werner Lechner
    Improved Medical Diagnostics IMD GmbH, Donauwoerth, Germany.
  • Rainer-Georg Siefen
    University Children's Hospital, Ruhr-University Bochum, Bochum, Germany.
  • Christina Lampe
    ZSEGI Centre for Rare Diseases of the University Hospital Gießen, Gießen, Germany.
  • Peter Nordbeck
    University and University Hospital Würzburg, Germany (P. Nordbeck).
  • Lorenz Grigull
    Department of Pediatric Hematology and Oncology, Hannover Medical School, Hannover, Germany.
  • Thomas Lücke
    University Hospital of Paediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr University Bochum, Bochum, Germany.

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