Neurofuzzy and EUFABES as tools for knowledge discovery in visual field data

被引：0

作者：

Zahlmann, G ^{[1
]}

Scherf, M ^{[1
]}

Wegner, A ^{[1
]}

机构：

[1] GSF Forschungszentrum Umwelt & Gesundheit, Medis, D-85764 Neuherberg, Germany

来源：

PROCEEDINGS OF THE 20TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 20, PTS 1-6: BIOMEDICAL ENGINEERING TOWARDS THE YEAR 2000 AND BEYOND | 1998年 / 20卷

关键词：

neurofuzzy; feature selection; knowledge discovery; ophthalmology;

D O I：

暂无

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

A knowledge based glaucoma monitor based on papilla findings, intraocular pressure and visual held data has been developed successfully. To explain and interpret the classifier decision concerning the visual field data in the single decision and over time a neurofuzzy approach has been applied. A distance based feature selection approach is used to find a feature subset which leads to Hell separated classes in the measurement space. It is also used as first step to get clusters of interest for neurofuzzy interpretation.

引用

页码：1360 / 1362

页数：3

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