Etracker Debug:
	et_pagename = "Journal of Intelligent Systems|jisys|C|[EN]"
Jump to ContentJump to Main Navigation

Journal of Intelligent Systems

Editor-in-Chief: Fleyeh, Hasan

4 Issues per year



Applied Artificial Intelligence Techniques for Identifying the Lazy Eye Vision Disorder

Patrick G. Clark1 / 1 / Gerhard W. Cibis2

1Department of Electrical Engineering and Computer Science, The University of Kansas, Lawrence, KS 66045, USA.

2Cibis Eye Care, Kansas City, MO 64112, USA.

Citation Information: Journal of Intelligent Systems. Volume 20, Issue 2, Pages 101–127, ISSN (Online) 2191-026X, ISSN (Print) 0334-1860, DOI: 10.1515/jisys.2011.007, June 2011

Publication History

Published Online:


Amblyopia, or lazy eye, is a neurological vision disorder that studies have shown to affect two to five percent of the population. Current methods of treatment produce the best visual outcome, if the condition is identified early in the patient's life. Several early screening procedures are aimed at finding the condition while the patient is a child, including an automated vision screening system. This paper aims to use artificial intelligence techniques to automatically identify children who are at risk for developing the amblyopic condition and should therefore be referred to a specialist, i.e., pediatric ophthalmologist. Three techniques, namely, decision tree learning, random forest, and artificial neural network, are studied in this paper in terms of their effectiveness, using metrics of sensitivity, specificity, and accuracy. The features used by the techniques are extracted from images of patient eyes and are based on the color information. The efficacy of pixel color data is investigated with respect to the measurement of the rate of change of the color in the iris and pupil, i.e., color slope features. A 10-fold stratified cross validation procedure is used to compare the effectiveness of the three AI techniques in this medical application domain.

Keywords.: Applied artificial intelligence; pattern analysis; decision tree; random forest; artificial neural network; lazy eye; amblyopia

Comments (0)

Please log in or register to comment.
Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.