基于数据挖掘算法的心脏病预测与分析

N. K, S. S., S. S
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引用次数: 0

摘要

心脏病是指一系列与心脏有关的健康问题。心脏病是目前世界上最严重的公共卫生问题。许多组织已经广泛使用了数据挖掘。医疗保健领域的数据挖掘即使不是极其重要,也正在成为一种潮流。如今,卫生部门产生了大量关于个人、疾病诊断、临床记录、医疗设备等方面的复杂数据。目的是了解已经发展到预测心脏问题的各种数据挖掘方法。根据研究结果,具有15个特征的随机森林超过了所有此类数据挖掘方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction and Analysis of Heart disease using Data mining Algorithms
Heart Disease refers to a broad range of heart-related health problems. Heart disease is currently the world's most serious public health issue. Many organizations have made extensive use of data mining. Data mining in healthcare is becoming trendy, if not extremely important. The health sector nowadays produces a significant volume of complex data about individuals, diagnosis of diseases, clinical notes, medical equipment, and so on. The objective is to know about the various data mining methods that have evolved to forecast heart problems. According to the findings, a Random forest with 15 features outstripped all such data-mining methods.
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