基于数据挖掘技术的中医药研究需求系统设计

Yuzhu Yang, Yining Huang, Linjing Yang, Hongxing Liu
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引用次数: 0

摘要

作为我国的国粹之一,中医在过去的几十年里经历了几次重大的变化。目前,中医药研究主要依靠传统经验。在数据挖掘技术的指导下,对中医进行研究具有十分重要的意义。人们对医疗服务、健康管理和疾病控制的要求越来越高,因此有必要对中医研究的相关方面进行深入研究。本文主要采用实验分析和关联挖掘的方法来研究中药研究的方向和重要性。实验结果表明,本文设计的系统中对象的平均处理时间小于6s,并发对象的数量可以满足基本要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of TCM Research Demand System Based on Data Mining Technology
As one of the quintessences of our country, TCM has experienced several major changes in the past decades. At present, Chinese medicine research mainly depends on traditional experience. Under the data mining technology, it is very important and meaningful to study Chinese medicine. People have higher and higher requirements for medical services, health management and disease control, so it is necessary to conduct in-depth research on relevant aspects of TCM research. This paper mainly uses experimental analysis and association mining to study the direction and importance of TCM research. The experimental results show that the average time for objects in the system designed in this paper is less than 6s, and the number of concurrent objects can meet the basic requirements.
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