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Evaluating the efficacy of bioelectrical impedance analysis using machine learning models for the classification of goats exposed to Haemonchosis.

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Title: Evaluating the efficacy of bioelectrical impedance analysis using machine learning models for the classification of goats exposed to Haemonchosis.
Authors: Siddique A; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Batchu P; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Shaik A; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Gurrapu P; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Erukulla TT; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Ellington C; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Rubio Villa AL; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Brown D; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Mahapatra A; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States., Panda S; Institute for Environmental Spatial Analysis, University of North Georgia, Oakwood, GA, United States., Morgan E; Institute for Global Food Security, Queen's University, Belfast, United Kingdom., Van Wyk J; Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, South Africa., Shapiro-Ilan D; United States Department of Agriculture- Agriculture Research Services, Fruit and Tree Nut Research, Byron, GA, United States., Kannan G; Department of Poultry Sciences, Auburn University, Auburn, AL, United States., Terrill TH; Department of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Source: Frontiers in veterinary science [Front Vet Sci] 2025 May 30; Vol. 12, pp. 1584828. Date of Electronic Publication: 2025 May 30 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101666658 Publication Model: eCollection Cited Medium: Print ISSN: 2297-1769 (Print) Linking ISSN: 22971769 NLM ISO Abbreviation: Front Vet Sci Subsets: PubMed not MEDLINE
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