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Association rule analysis in cardiovascular disease

机译:心血管疾病的关联规则分析

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摘要

Data mining in healthcare is a rising field due to the vast amount of patient specific data which is freely available for analysis. While the majority of this data has been analyzed using various data mining techniques like classification, but association rule mining in this field is still largely unexplored. Association Rule Mining is a simple yet powerful tool that brings to light hidden relationships among data attributes in addition to statistically validating those which are already known. These relationships can help in understanding diseases and their causes in a better way, which in turn will help to prevent them. This report presents exploration of this field and the conclusions drawn from analyzing heart disease dataset from UCI repository. In this paper association rule mining is applied to cardiovascular disease. Cardiovascular diseases are diseases related to heart and circulatory system. Heart disease is explored in this paper.
机译:由于大量可免费用于分析的患者特定数据,医疗保健中的数据挖掘是一个新兴领域。尽管已使用各种数据挖掘技术(例如分类)对大多数数据进行了分析,但是在该领域中的关联规则挖掘仍处于很大程度上未开发的状态。关联规则挖掘是一种简单但功能强大的工具,除了可以对已知属性进行统计验证之外,还可以揭示数据属性之间的隐藏关系。这些关系有助于更好地理解疾病及其病因,进而有助于预防疾病。本报告介绍了该领域的探索以及通过分析UCI存储库中的心脏病数据集得出的结论。本文将关联规则挖掘应用于心血管疾病。心血管疾病是与心脏和循环系统有关的疾病。本文探讨了心脏病。

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