机器学习在奶牛临床疾病预测中的应用

Application of Machine Learning for Prediction of Clinical Disease in Dairy Cows

机器学习是指计算机通过大量数据训练及分析来模拟人类的学习行为,从而获得新的知识和技能,是人工智能的核心。近年来,机器学习在奶牛疾病预测领域的应用已成为国际上的研究热点。论文介绍了利用奶牛机体生理指标和生产数据建立奶牛疾病预测模型的方法,重点阐述了如何利用决策树和神经网络筛选奶牛疾病风险因子、预测疾病和疾病分类。同时,综述了机器学习预测代谢性疾病、跛行、乳房炎、热应激和传染性疾病的进展。

The concept of machine learning refers to a computer that simulates human learning behavior through a large amount of data training and analysis to obtain new knowledge and skills.Machine learning is the core of artificial intelligence.In recent years,the research of machine learning in the field of dairy cow disease prediction has become a hot topic in the world.This paper introduced the method of establishing dairy cow disease prediction model by using physiological indicators and production data of dairy cow.The approach to use decision trees and neural networks to select disease risk factors,predict diseases and classify diseases was stressed.At the same time,the progress of machine learning in predicting metabolic diseases,lameness,mastitis,heat stress and infectious diseases was reviewed.