Web based decision support system for eye movement disorder diagnosis

Abstract

BACKGROUND:

Recently, acupuncture of Traditional Chinese Medicine (TCM) becomes a better method compared with the western medicine for treating eye movement disorder. However, because therapeutic mechanism of TCM is very complicated, acupuncture of TCM depends on the doctor's experience to a large extent.

INTRODUCTION:

A Decision Support System (DSS) is urgently needed to carry out Computer Aided Diagnosis (CAD) in order to provide doctors with required clinical reference.

MATERIALS AND METHODS:

Save the data obtained by diplopia image test software to the database, and then upload the data from various data centers to the DSS which is based on Support Vector Machine (SVM) optimized by Particle Swarm Optimization (PSO) through the Web interface. Train these data to obtain a classification model with high accuracy, then download this classification model back to every data center to help them make classification prediction for new test samples, realizing CAD of eye movement disorder.

RESULTS:

The test software can get the diplopia images and test data quickly, and then the test data can be successfully stored to the database for future retrieve. Moreover the DSS can achieve the CAD with good results.

DISCUSSION:

The rounded software system can realize its expectant functions. It can get accurate classification model quickly. The accuracy of classification is increased to 62.5%.

CONCLUSIONS:

The feasibility and accuracy of this DSS was proved by clinical experiments with good results. So it can be applied to provide CAD for eye movement disorder in hospitals.