Prediction of VLDL cholesterol value with machine learning techniques

Abstract

Cholesterol is an oil-like substance that is found in the membranes of animal cells and also carried in blood plasma, which has some vital functions in the human body, especially in the endocrine and digestive systems. Very Low-Density Lipoprotein (VLDL) is a lipid that is not gained with nutrients, instead produced by the body itself. However, it is considered to be in the bad cholesterol group since this type of cholesterol threatens cardiovascular health. As a result, it is normally expected to be at the lowest levels in the human body. In this study, It is applied some machine learning techniques to estimate VLDL Cholesterol value by some attributes such as age, sex, creatinine, aspartat transaminaz (AST), alanine transaminaz (ALT), free t4, glucose, and triglyceride. In this, the techniques include the Generalized Linear Model (GLM), Decision Tree (DT), and Gradient Boosted Trees (GBT). It is computed that GLM has the root-mean-squared-error value 0.655 and the correlation value 1.0 so consequently returns the best results compared to others.