摘要
数据挖掘是一个利用各种分析工具在海量数据中发现模型和数据间关系的过程。临床医学上大量的数据中蕴含着丰富的信息。利用数据挖掘技术,特别是基于粗糙集理论的数据挖掘技术,通过数据训练集所训练得到的算法模型能够有效应用于疾病诊断,并获得很高的准确率。本文简要介绍了数据挖掘技术的基本原理和主要方法,以及粗糙集理论的基本原理,并给出了一个利用数据挖掘技术对肺部肿瘤进行诊断评价的应用实例。
Data mining is a type of process,which uses all kinds of analytical tools to search the relationship between the model and data in the sea of data. The data obtained from the clinical diagnosis contain a large amount of information. The algorithm which uses the data mining technique,especially the technique based on the rough set theory,can be trained through the training data set and can be applied to determine the state of an illness with a very high accuracy. This paper briefly introduces the principles and methods of the data mining and the rough set theory,and gives an example on the diagnosis and evaluation of the lung tumor.
出处
《上海生物医学工程》
2002年第2期3-7,共5页
Shanghai Journal of Biomedical Engineering
基金
国家自然科学基金(30170259)
辽宁省科学技术基金(2001101057)
教育部留学回国启动基金
关键词
临床医学
诊断
数据挖掘
肺癌诊断
粗糙集
神经网络
决策树
data mining lung cancer diagnosis rough set theory neural network decision-making tree
