Neural network-based diagnosing for optic nerve disease from visual-evoked potential.
In this paper, we purpose a diagnostic procedure to identify the optic nerve disease from visual evoked potential (VEP) signals using an Artificial Neural Network (ANN). Multilayer feed forward ANN trained with a Levenberg Marquart backpropagation algorithm was implemented. The correct classification rate was 96.87% for subjects having optic nerve disease and 96.66% for healthy subjects. The end results are classified as healthy and diseased. Testing results were found to be compliant with the expected results that are derived from the physician's direct diagnosis, angiography, VEP and pattern electroretinography. The stated results show that the proposed method could point out the ability of design of a new intelligent assistance diagnosis system.
Kara
Sadik
S
Department of Electrical and Electronics Eng., Erciyes University, 38039 Kayseri, Turkey. kara@erciyes.edu.tr
Güven
Ayşegül
A
D000328:Adult; D000465:Algorithms; D005074:Evoked Potentials, Visual; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D009901:Optic Nerve Diseases / Q000175:diagnosis* / Q000503:physiopathology