1 results match your criteria: "WHO Collaborating Centre for Leishmaniasis. Spanish National Centre for Microbiology[Affiliation]"
Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan.
PLoS Negl Trop Dis
March 2025
WHO Collaborating Centre for Leishmaniasis. Spanish National Centre for Microbiology, Instituto de Salud Carlos III, Majadahonda (Madrid), Spain.
Background: Post-kala-azar dermal leishmaniasis (PKDL) appears as a rash in some individuals who have recovered from visceral leishmaniasis caused by Leishmania donovani. Today, basic knowledge of this neglected disease and how to predict its progression remain largely unknown.
Methods And Findings: This study addresses the use of several biochemical, haematological and immunological variables, independently or through unsupervised machine learning (ML), to predict PKDL progression risk.