An optimized MLP model to diagnosis the bipolar disorder

Abstract

The use of artificial neural networks in different areas of engineering science is growing by the day. The significant proportions of research in medical engineering, Therefore in this paper have tried to implemented MLP model with 47 parameters for diagnosis of bipolar disorder. Parameters such as: lack of pleasure, feelings of guilt, worthlessness, lack of success, mental anxiety, somatic anxiety disorder, the disorder of interest, etc. in next part, we done the manipulation structure of MLP model, for this work switching the function in layers. And comparing the error of manipulation structure with previous manipulation. We concluded with using purelin function in layers, the error of diagnosis reduces 4% and this value is an acceptable value.