基于C4.5决策树算法的弱视诊断模型  

Amblyopia diagnosis model based on C4.5 decision tree algorithm

作　　者：王丽萍[1] 蒋琴飞[1] 

机构地区：[1]浙江工业大学信息学院,浙江杭州310014

出　　处：《机电工程》2009年第7期61-64,共4页Journal of Mechanical & Electrical Engineering

基　　金：浙江省重大科技攻关项目(2006C11223);浙江省自然科学基金杰出青年团队项目(R2080100)

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(P-VEP)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。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 pattern-visual evoked potential （P-VEP）. Several amblyopia diagnoses models were established from that. The test results in- dicate that these models can guide doctors with a higher accuracy to make amblyopia diagnosis and treatment, improve the diagnose efficiency, and help patients to self-test.

关 键 词：弱视 图形视诱发电位 C4.5 决策树 模型 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]