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Lactose Intolerance Prediction Using Artificial Neural Networks

机译:利用人工神经网络的乳糖不耐预测

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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.
机译:本文提出了一种用于乳糖不耐预测预测的人工神经网络。系统输入信息是从波斯尼亚和黑塞哥维那的一百个人填充的有关问卷的症状相关问题和答案。参与者在LCT 13910 C / T和LCT 22018g / A多态性上进行基因分型,其是可靠的乳糖容差/不容忍的预测因子,并且该信息是神经网络的输出。 ANN由6个输入参数组成,将贝叶斯调节训练算法提供信息。 ANN性能评估用100个基因分型样品中的10个样品进行,结果预测了一个人是否是乳糖耐受性或乳糖不耐受。本文提出的人工神经网络的目的是帮助乳糖不耐受预测的专家,避免在临床实践中不必要的进一步实验室和遗传测试。

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