摘要
医疗行业的发展扩大了医疗数据信息种类与数量,这将直接影响医院医疗水平与服务水平和医院核心竞争力。本文以医疗大数据为研究对象,提出了基于遗传算法的K-means 改进聚类方法,并以医疗费用数据为例展开分析,为提高医疗服务质量提供有效数据信息。
Abstract
With the development of medical industry, the types and quantity of medical data information have been expanded,which will directly affect the medical level and service level of hospitals and its core competitiveness. In this paper, taking medical big data as the research object, we propose an improved K-means clustering method based on genetic algorithm, and take the medical expenses as an example for analysis, so as to provide effective data information for improving the quality of medical service.
关键词
数据挖掘技术 /
医疗大数据 /
遗传算法 /
K-means聚类
Key words
data mining technology /
medical big data /
genetic algorithm /
K-means clustering
陈闽韬, 匡芳君.
数据挖掘技术在医疗大数据中的应用研究[J]. 电脑与电信. 2017(11): 34-36
CHEN Min-tao, KUANG Fang-jun.
Research on the Application of Data Mining Technology in Medical Big Data[J]. Computer & Telecommunication. 2017(11): 34-36
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