Lactose Intolerance Prediction Using Artificial Neural Networks

被引：0

作者：

Spahic, Lemana ^{[1
]}

Sehovic, Emir ^{[1
]}

Secerovic, Alem ^{[1
]}

Dozic, Zerina ^{[1
]}

Smajlovic-Skenderagic, Lejla ^{[1
]}

机构：

[1] Int Burch Univ, Genet & Bioengn, Sarajevo 71210, Bosnia & Herceg

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING, CMBEBIH 2019 | 2020年 / 73卷

关键词：

Lactose intolerance; Artificial neural network; Genotype; Diagnosis; Prediction; LACTASE-PHLORHIZIN HYDROLASE; ADULT-TYPE HYPOLACTASIA; GENE; PERSISTENCE; CLASSIFICATION; BIOSYNTHESIS; DEFICIENCY;

D O I：

10.1007/978-3-030-17971-7_75

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

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.

引用

页码：505 / 510

页数：6

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