Applying artificial intelligence to rare diseases: a literature review highlighting lessons from Fabry disease.

Journal: Orphanet journal of rare diseases
PMID:

Abstract

BACKGROUND: Use of artificial intelligence (AI) in rare diseases has grown rapidly in recent years. In this review we have outlined the most common machine-learning and deep-learning methods currently being used to classify and analyse large amounts of data, such as standardized images or specific text in electronic health records. To illustrate how these methods have been adapted or developed for use with rare diseases, we have focused on Fabry disease, an X-linked genetic disorder caused by lysosomal α-galactosidase. A deficiency that can result in multiple organ damage.

Authors

  • Dominique P Germain
    Division of Medical Genetics, University of Versailles-St Quentin en Yvelines (UVSQ), Paris-Saclay University, 2 avenue de la Source de la Bièvre, 78180, Montigny, France. dominique.germain@uvsq.fr.
  • David Gruson
    Chaire santé de l'Institut d'études politiques de Paris, Ethik-IA, Paris, France.
  • Marie Malcles
    Takeda France SAS, 75116, Paris, France.
  • Nicolas Garcelon
    Plateforme data science - institut des maladies génétiques Imagine, Inserm, centre de recherche des Cordeliers, UMR 1138 équipe 22, institut Imagine, Paris-Descartes, université Sorbonne- Paris Cité, Paris, France.