基于C4.5决策树算法的弱视诊断模型

作者：王丽萍,蒋琴飞 日期：2009-08-18/span> 浏览：3620 查看PDF文档

基于C4.5决策树算法的弱视诊断模型

王丽萍,蒋琴飞
(浙江工业大学 信息学院,浙江 杭州 310014)

摘要：针对目前的弱视诊断方法大多采用主观检查的方法，存在效率低且依赖于医生专业知识和临床经验的问题，使用VISTON基于图形视诱发电位（PVEP）的弱视诊断和治疗仪，在浙江省某家大型医院的眼科中心对137例弱视患者以及23例正常人进行了检测，对记录的数据采用C4.5决策树算法进行了分类，建立了弱视诊断模型。实际检测结果数据表明，该模型能够以较高的准确率辅助医生进行弱视诊断和治疗，提高了诊断效率，并有助于患者自查。
关键词：弱视；图形视诱发电位；C4.5；决策树；模型
中图分类号：TP274文献标识码：A文章编号：1001-4551(2009)07-0061-04

Amblyopia diagnosis model based on C4.5 decision tree algorithm
WANG Liping, JIANG Qinfei
(College of Information Engineering, Zhejiang University of Technology, Hangzhou 310014, China)
Abstract: In order to improve the accuracy and efficiency of amblyopia diagnoses, C4.5 decision tree classification algorithm was employed to modeling through a set of the real recorded data. These data were collected from 137 cases of patients with amblyopia as well as 23 cases with normal at a large hospital in Zhejiang Province, using VISTON diagnosis and treatment device based on the patternvisual evoked potential (PVEP). Several amblyopia diagnoses models were established from that. The test results indicate that these models can guide doctors with a higher accuracy to make amblyopia diagnosis and treatment, improve the diagnose efficiency, and help patients to selftest.
Key words: amblyopia; patternvisual evoked potential (PVEP); C4.5; decision tree; model
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