Machine learning approaches classify clinical malaria outcomes based on haematological parameters.

Journal: BMC medicine
Published Date: Nov 30, 2020

Abstract

BACKGROUND: Malaria is still a major global health burden, with more than 3.2 billion people in 91 countries remaining at risk of the disease. Accurately distinguishing malaria from other diseases, especially uncomplicated malaria (UM) from non-malarial infections (nMI), remains a challenge. Furthermore, the success of rapid diagnostic tests (RDTs) is threatened by Pfhrp2/3 deletions and decreased sensitivity at low parasitaemia. Analysis of haematological indices can be used to support the identification of possible malaria cases for further diagnosis, especially in travellers returning from endemic areas. As a new application for precision medicine, we aimed to evaluate machine learning (ML) approaches that can accurately classify nMI, UM, and severe malaria (SM) using haematological parameters.

Authors

  • Collins M Morang'a
    West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Accra, Ghana.
  • Lucas Amenga-Etego
    West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Accra, Ghana. lamenga-etego@ug.edu.gh.
  • Saikou Y Bah
    West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Accra, Ghana.
  • Vincent Appiah
    West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Accra, Ghana.
  • Dominic S Y Amuzu
    West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Accra, Ghana.
  • Nicholas Amoako
    West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Accra, Ghana.
  • James Abugri
    Department of Applied Chemistry and Biochemistry, C. K Tedam University of Technology and Applied Sciences, Navrongo, Ghana.
  • Abraham R Oduro
    Ministry of Health, Navrongo Health Research Centre (NHRC), Navrongo, Ghana.
  • Aubrey J Cunnington
    Section of Pediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, UK.
  • Gordon A Awandare
    West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Accra, Ghana.
  • Thomas D Otto
    Institute of Infection, Immunity & Inflammation, MVLS, University of Glasgow, Glasgow, UK. Thomasdan.otto@glasgow.ac.uk.

Keywords

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