Machine learning prediction of multiple anthelmintic resistance and gastrointestinal nematode control in sheep flocks
Simone Cristina Méo Niciura,
Guilherme Martineli Sanches
Abstract:The high prevalence of Haemonchus contortus and its anthelmintic resistance have affected sheep production worldwide. Machine learning approaches are able to investigate the complex relationships among the factors involved in resistance. Classification trees were built to predict multidrug resistance from 36 management practices in 27 sheep flocks. Resistance to five anthelmintics was assessed using a fecal egg count reduction test (FECRT), and 20 flocks with FECRT < 80% for four or five anthelmintics were … Show more
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