Computational Diagnosis of Learning Disability

The paper proposes a perceptron based artificial neural network model for diagnosing learning disability using curriculum based test conducted by special educators in medical environment. The model comprises of a single input layer with eleven units which correspond to different sections of a conventional test and one output unit. The method is not only devoid of typical computational complexity and sophistication associated with other methods but gives comparable experimental results on detection measures like accuracy, sensitivity and specificity.