Machine learning approaches classify clinical malaria outcomes based on haematological parameters

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. Further...

Volledige beschrijving

Bewaard in:
Bibliografische gegevens
Gepubliceerd in:BMC Med
Hoofdauteurs: Morang’a, Collins M., Amenga–Etego, Lucas, Bah, Saikou Y., Appiah, Vincent, Amuzu, Dominic S. Y., Amoako, Nicholas, Abugri, James, Oduro, Abraham R., Cunnington, Aubrey J., Awandare, Gordon A., Otto, Thomas D.
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: BioMed Central 2020
Onderwerpen:
Research Article
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7702702/
https://ncbi.nlm.nih.gov/pubmed/33250058
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12916-020-01823-3
Tags: Voeg label toe
Geen labels, Wees de eerste die dit record labelt!

Gelijkaardige items