مقايسه پيش بيني انواع حاملگي با به كارگيري شبكه هاي عصبي مصنوعي و رگرسيون بحستيك چند جمله اي

Comparing predictions of type of pregnancy using artificial neural networks and multinomial logistic regression

Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. Type of pregnancy is one of them such that it has four possible states: wanted, wife unwanted, husband unwanted and couple unwanted. In this paper we have predicted type of pregnancy as influencing factors on it, using two different models and compared them together.Regarding type of pregnancy with several levels, we developed a multinomial logistic regression and a neural network based on data and compared their results using three statistical indices: sensitivity, Specificity and kappa.Based on three indices, neural network showed a better fit and prediction on data in comparison to multinomial logistic regression. When relations between variables are complex, one can use neural networks instead of multinomial logistic regression to predict nominal response variables with several levels in order to gain more accurate predictions.