Cattle Disease Auxiliary Diagnosis and Treatment System Based on Data Analysis and Mining

Abstract

With the rapid development of big data and artificial intelligence, data analysis and mining are becoming more and more widely used in animal husbandry. In this paper, a large number of multi-source cattle electronic medical record data are collected and used the data analysis and mining technology to realize the intelligent diagnosis system for cattle diseases. Firstly, the text preprocessing technology is used to remove the repetition on the cattle electronic medical record data, remove the stop words, word segmentation etc. the data is divided into a training set and a test set. The classifier is then constructed using a support vector machine (SVM) to classify the selected symptom words. Finally, the Apriori algorithm is used to correlate the specific disease name and the probability of the disease, giving the corresponding treatment plan. The system can treat the diseases in time, reduce the losses of herders effectively and realize the development of scientific intelligence in animal husbandry.