Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal...
Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan
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Publisher
United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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Scope and Contents
Contents
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.
This study addresses the use of several biochemical, haematological and immunolo...
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Full title
Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan
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TN_cdi_doaj_primary_oai_doaj_org_article_c2dba663d0f748b2b4a5944653c25b99
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c2dba663d0f748b2b4a5944653c25b99
Other Identifiers
ISSN
1935-2735,1935-2727
E-ISSN
1935-2735
DOI
10.1371/journal.pntd.0012924
