Lactose intolerance prediction using artificial neural networks

Abstract

An Artificial Neural Network for lactose intolerance prediction is presented in this paper. The system input information were symptom related questions and answers from a condition-oriented questionnaire, that was filled by one hundred individuals from Bosnia and Herzegovina. Participants were genotyped on LCT 13910 C/T and LCT 22018 G/A polymorphisms, which are reliable predictors of lactose tolerance/intolerance, and that information was the output of the neural network. The ANN consisted of 6 input parameters, that feed the Bayesian regulation training algorithm with information. ANN performance evaluation was performed with 10 samples out of 100 genotyped samples and the results predict whether a person is lactose tolerant or lactose intolerant. The aim of the artificial neural network presented in this paper is to assist specialists in lactose intolerance prediction, avoiding unnecessary further laboratory and genetic testing in clinical practice.