MALrisk: a machine-learning-based tool to predict imported malaria in returned travellers with fever.

Journal: Journal of travel medicine
PMID: 38578987

Abstract

BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence could improve the management of febrile travellers.

Authors

  • Leire Balerdi-Sarasola
    ISGlobal, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain.
  • Pedro Fleitas
    ISGlobal, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain.
  • Emmanuel Bottieau
    Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
  • Blaise Genton
    Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
  • Paula Petrone
    Barcelona Institute for Global Health (ISGlobal), C/ del Dr. Aiguader, 88, Barcelona 08003, Catalonia, Spain. Electronic address: paula.petrone@isglobal.org.
  • José Muñoz
    Barcelona Institute for Global Health (ISGlobal), Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.
  • Daniel Camprubí-Ferrer
    ISGlobal, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain.

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