Utilization of artificial neural networks in the diagnosis of optic nerve diseases.
This research is concentrated on the diagnosis of optic nerve disease through the analysis of pattern electroretinography (PERG) signals with the help of artificial neural network (ANN). Multilayer feed forward ANN trained with a Levenberg Marquart (LM) backpropagation algorithm was implemented. The designed classification structure has about 96.4% sensitivity, 90.4% specifity and positive prediction is calculated to be 94.2%. 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. The end benefit would be to assist the physician to make the final decision without hesitation.
Kara
Sadik
S
Department of Electrical and Electronics Engineering, Erciyes University, 38039 Kayseri, Turkey. kara@erciyes.edu.tr
Güven
Ayşegül
A
Oner
Ayşe Oztürk
AO
D000328:Adult; D000368:Aged; D000465:Algorithms; D016022:Case-Control Studies; D004596:Electroretinography / Q000379:methods*; D005074:Evoked Potentials, Visual; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D009901:Optic Nerve Diseases / Q000175:diagnosis*; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted