Differential diagnosis of infectious reproductive diseases in sheep flocks of Mato Grosso State, Brazil

Eckstein, Camila; Moustacas, Valéria Spyridion; Lopes, Luciano Bastos; Mol, Juliana Pinto da Silva; Gomes, S. C.; Santos, Rafael dos; Castro, Bruno Gomes de; Santos, Renato Lima

doi:10.1016/j.smallrumres.2017.06.015

Small Ruminant Research

2017

DOI: 10.1016/j.smallrumres.2017.06.015

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Differential diagnosis of infectious reproductive diseases in sheep flocks of Mato Grosso State, Brazil

Camila Eckstein

Valéria Spyridion Moustacas

Luciano Bastos Lopes

et al.

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Cited by 2 publications

References 22 publications

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Rapid and non‐invasive detection of cystic echinococcosis in sheep based on serum fluorescence spectrum combined with machine learning algorithms

Xu,

Dawuti,

Maimaitiaili

et al. 2024

Journal of Biophotonics

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Cystic echinococcosis (CE) is a grievous zoonotic parasitic disease. Currently, the traditional technology of screening CE is laborious and expensive, developing an innovative technology is urgent. In this study, we combined serum fluorescence spectroscopy with machine learning algorithms to develop an innovative screening technique to diagnose CE in sheep. Serum fluorescence spectra of Echinococcus granulosus sensu stricto‐infected group (n = 63) and uninfected E. granulosus s.s. group (n = 60) under excitation at 405 nm were recorded. The linear support vector machine (Linear SVM), Quadratic SVM, medium radial basis function (RBF) SVM, K‐nearest neighbor (KNN), and principal component analysis‐linear discriminant analysis (PCA‐LDA) were used to analyze the spectra data. The results showed that Quadratic SVM had the great classification capacity, its sensitivity, specificity, and accuracy were 85.0%, 93.8%, and 88.9%, respectively. In short, serum fluorescence spectroscopy combined with Quadratic SVM algorithm has great potential in the innovative diagnosis of CE in sheep.

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Rapid and non‐invasive detection of cystic echinococcosis in sheep based on serum fluorescence spectrum combined with machine learning algorithms

Xu,

Dawuti,

Maimaitiaili

et al. 2024

Journal of Biophotonics

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Microbiological, molecular, and histopathological findings in goats experimentally infected with Actinobacillus seminis

Santos

Costa

Silva

et al. 2019

Microbial Pathogenesis

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Differential diagnosis of infectious reproductive diseases in sheep flocks of Mato Grosso State, Brazil

Cited by 2 publications

References 22 publications

Rapid and non‐invasive detection of cystic echinococcosis in sheep based on serum fluorescence spectrum combined with machine learning algorithms

Rapid and non‐invasive detection of cystic echinococcosis in sheep based on serum fluorescence spectrum combined with machine learning algorithms

Microbiological, molecular, and histopathological findings in goats experimentally infected with Actinobacillus seminis

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