基于蒙古族农牧民高血压大数据的可视化分析与机器学习算法应用比较研究

Visual Analysis and Comparative Study on Application of Machine Learning Algorithm Based on Big Data of Mongolian Farmers and Herdsmen with Hypertension

以内蒙古某旗县蒙古族农牧民高血压患者数据为例,使用Python程序设计语言,实现非结构化文本数据的分词与统计以及高血压大数据的可视化分析处理,并通过KNN、朴素贝叶斯算法、随机森林分类等机器学习算法对病例数据分别训练,并对诊断结果进行预测,找出适合此数据集的机器学习预测模型,为高血压的预防、诊断、治疗提供辅助决策。同时,提出了针对其他慢病大数据分析的建议方案。

This paper takes the hypertension patient data of Mongolian farmers and herdsmen in a county in Inner Mongolia as an example,Python programming language is used to realize word segmentation and statistics of unstructured text data and visual analysis and processing of hypertension big data.KNN,Naive Bayes algorithm,random forest classification and other machine learning algorithms were used to train the case data respectively,and to predict the diagnosis results,to find out the machine learning prediction model suitable for this data set,and to provide auxiliary decision-making for the prevention,diagnosis and treatment of hypertension.At the same time,this paper puts forward some suggestions for big data analysis of other chronic diseases.