Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan.

Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan.

<h4>Background</h4>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.<...

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Main Authors: Ana Torres, Brima Musa Younis, Samuel Tesema, Jose Carlos Solana, Javier Moreno, Antonio J Martín-Galiano, Ahmed Mudawi Musa, Fabiana Alves, Eugenia Carrillo
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-03-01
Series:PLoS Neglected Tropical Diseases
Online Access:https://doi.org/10.1371/journal.pntd.0012924
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https://doi.org/10.1371/journal.pntd.0012924

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