Ushikubo S, Kubota C, Ohwada H. The Early Detection of Subclinical Ketosis in Dairy Cows Using Machine Learning Methods. ICMLC '17: Proceedings of the 9th International Conference on Machine Learning and Computing. 2017;38-42. https://doi.org/10.1145/3055635.3056625.
This study evaluated machine learning methods for the early detection of subclinical ketosis in dairy cows using daily dairy data from 75 cows. Subclinical ketosis, which lacks obvious symptoms, is challenging for farmers and veterinarians to diagnose, but early detection is crucial for preventing milk production losses. Among the machine learning classifiers tested, Support Vector Machines (SVM) showed the best performance with a recall score of 0.926 during cross-validation. The selected features for the prediction model were validated as appropriate based on previous research
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