The use of machine learning in rare diseases: a scoping review.

Journal: Orphanet journal of rare diseases
Published Date:

Abstract

BACKGROUND: Emerging machine learning technologies are beginning to transform medicine and healthcare and could also improve the diagnosis and treatment of rare diseases. Currently, there are no systematic reviews that investigate, from a general perspective, how machine learning is used in a rare disease context. This scoping review aims to address this gap and explores the use of machine learning in rare diseases, investigating, for example, in which rare diseases machine learning is applied, which types of algorithms and input data are used or which medical applications (e.g., diagnosis, prognosis or treatment) are studied.

Authors

  • Julia Schaefer
    Technische Universität Berlin, Berlin, Germany.
  • Moritz Lehne
    Berlin Institute of Health (BIH), Berlin, Germany. moritz.lehne@bihealth.de.
  • Josef Schepers
    Berlin Institute of Health (BIH), Berlin, Germany.
  • Fabian Prasser
    Berlin Institute of Health (BIH), Berlin, Germany.
  • Sylvia Thun
    Charité Universitätsmedizin, Berlin Institute of Health, Germany.