Diagnosis of the macular diseases from pattern electroretinography signals using artificial neural networks

In this paper, we purpose a diagnostic procedure to identify the macular disease from pattern electroretionography (PERG) signals using artificial neural networks (ANN) methods. Multilayer feed forward ANN trained with a Levenberg Marquart backpropagation algorithm was implemented. The designed classification structure has about 96% sensitivity, 100% specifity and correct classification is calculated to be 98%. 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 and Arden ratio of electrooculogram (EOG). The stated results show that the proposed method could point out the ability of design of a new intelligent assistance diagnosis system.