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医学数据中关联规则的发现。

Discovery of association rules in medical data.

作者信息

Doddi S, Marathe A, Ravi S S, Torney D C

机构信息

Los Alamos National Laboratory, NM 87545, USA.

出版信息

Med Inform Internet Med. 2001 Jan-Mar;26(1):25-33.

Abstract

Data mining is a technique for discovering useful information from large databases. This technique is currently being profitably used by a number of industries. A common approach for information discovery is to identify association rules which reveal relationships among different items. In this paper, we use this approach to analyse a large database containing medical-record data. Our aim is to obtain association rules indicating relationships between procedures performed on a patient and the reported diagnoses. Random sampling was used to obtain these association rules. After reviewing the basic concepts associated with data mining, we discuss our approach for identifying association rules and report on the rules generated.

摘要

数据挖掘是一种从大型数据库中发现有用信息的技术。目前,许多行业都在成功地使用这项技术。信息发现的一种常见方法是识别揭示不同项目之间关系的关联规则。在本文中,我们使用这种方法来分析一个包含病历数据的大型数据库。我们的目标是获得表明对患者进行的手术与报告的诊断之间关系的关联规则。使用随机抽样来获取这些关联规则。在回顾了与数据挖掘相关的基本概念之后,我们讨论了识别关联规则的方法,并报告了生成的规则。

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