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The successful control of the disease depends on its accurate and early diagnosis, which is usually made by combining clinical symptoms with laboratory tests such as serological, parasitological, and molecular tests. However, early diagnosis based on serological tests may exhibit low accuracy due to lack of specificity caused by cross\u2010reactivities with other pathogens, and sensitivity issues related, among other reasons, to disease stage, leading to misdiagnosis. In this study was investigated the use of mid\u2010infrared spectroscopy and multivariate analysis to perform a fast, accurate, and easy canine visceral leishmaniasis diagnosis. Canine blood sera of 20 noninfected, 20 <jats:italic>Leishmania infantum<\/jats:italic>, and eight <jats:italic>Trypanosoma evansi<\/jats:italic> infected dogs were studied. The data demonstrate that principal component analysis with machine learning algorithms achieved an overall accuracy above 85% in the diagnosis.<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/jbio202100141-gra-0001.png\" xlink:title=\"image\"\/><\/jats:p>","DOI":"10.1002\/jbio.202100141","type":"journal-article","created":{"date-parts":[[2021,8,23]],"date-time":"2021-08-23T11:33:42Z","timestamp":1629718422000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["A new strategy for canine visceral leishmaniasis diagnosis based on <scp>FTIR<\/scp> spectroscopy and machine learning"],"prefix":"10.1002","volume":"14","author":[{"given":"Gustavo","family":"Larios","sequence":"first","affiliation":[{"name":"Grupo de \u00d3ptica e Fot\u00f4nica, Instituto de F\u00edsica Universidade Federal de Mato Grosso do Sul  Campo Grande 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