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A Gene Prediction Function for Type 2 Diabetes Mellitus using Logistic Regression
Conference proceeding

A Gene Prediction Function for Type 2 Diabetes Mellitus using Logistic Regression

Hala Alshamlan, Hind Bin Taleb, Areej Al Sahow and IEEE
2020 11TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION SYSTEMS (ICICS), pp.038-041
International Conference on Information and Communication Systems
01/01/2020
DOI: https://doi.org/10.1109/ICICS49469.2020.239549

Abstract

Computer Science Computer Science, Theory & Methods Engineering Engineering, Electrical & Electronic Science & Technology Technology Telecommunications
Type 2 diabetes mellitus (T2D), is a complex diabetes disease that is caused by high blood sugar, insulin resistance, and a relative lack of insulin. Many studies are trying to predict variant genes that causes this disease by using a sample disease model. In this paper we predict diabetic and normal persons by using fisher score feature selection, chi-2 feature selection and Logistic Regression supervised learning algorithm with best accuracy of 90.23%.

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