[1]戴晓敏,丁 勇.分类算法在高血压诊断中的应用研究[J].医学信息,2019,32(01):1-3.[doi:10.3969/j.issn.1006-1959.2019.01.001]
　DAI Xiao-min,DING Yong.Application of Classification Algorithm in Diagnosis of Hypertension[J].Journal of Medical Information,2019,32(01):1-3.[doi:10.3969/j.issn.1006-1959.2019.01.001]
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分类算法在高血压诊断中的应用研究()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
32卷
期数:
2019年01期
页码:
1-3
栏目:
出版日期:
2019-01-01

文章信息/Info

Title:
Application of Classification Algorithm in Diagnosis of Hypertension
文章编号:
1006-1959（2019）01-0001-03
作者:
戴晓敏1; 丁 勇2
1.上海市浦东新区周浦医院心血管内科，上海 200120；2.南京理工大学泰州科技学院，江苏 泰州 225300
Author(s):
DAI Xiao-min1; DING Yong2
1.Department of Cardiology,Zhoupu Hospital,Pudong New Area,Shanghai 200120,China;2.Taizhou Institute of Science and Technology,Nanjing University of Science and Technology, Taizhou 225300,Jiangsu,China
关键词:
高血压; 决策树; 分类; C4.5; GLU; TC; TG
Keywords:
Hypertension; Decision tree; Classification; C4.5; GLU; TC; TG
分类号:
R319
DOI:
10.3969/j.issn.1006-1959.2019.01.001
文献标志码:
A
摘要:
高血压作为一种严重影响人类健康的心脑血管疾病，越来越得到人们的重视，如何利用数据挖掘技术从大量的病例中发现潜在的发病机理成为生物信息学研究的热点。本文首先采用数据清理、变换等预处理技术对医院提供的大量生化检验数据进行处理，提取GLU、TC、TG等影响高血压的主要生理体征属性；然后，针对C4.5算法在体征属性选择方面存在的偏离问题，引入属性权重的概念，对C4.5算法进行改进；最后，基于改进的C4.5算法构建决策树，并从中提取用于诊断的分类规则。实验证明，构建的决策树模型符合医学认识，准确率较高，为辅助医生诊断和治疗高血压疾病提供了有力的科学依据。
Abstract:
As a cardiovascular and cerebrovascular disease that seriously affects human health, hypertension has been paid more and more attention. How to use data mining technology to discover potential pathogenesis from a large number of cases has become a hot spot in bioinformatics research. In this paper, the data processing, transformation and other pre-processing techniques are used to process the large amount of biochemical test data provided by the hospital, and the main physiological signs of hypertension, such as GLU, TC and TG, are extracted. Then, for the deviation problem of C4.5 algorithm in the selection of the attribute of the sign, the concept of attribute weight is introduced to improve the C4.5 algorithm. Finally, the decision tree is constructed based on the improved C4.5 algorithm and extracted for diagnosis classification rules.The experiment proves that the constructed decision tree model is in line with medical knowledge and has high accuracy, which provides a powerful scientific basis for assisting doctors in the diagnosis and treatment of hypertension.

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更新日期/Last Update: 2019-01-22