Prediction of LDL in hypertriglyceridemic subjects using an innovative ensemble machine learning technique

Abstract

Determining low-density lipoprotein (LDL) is a costly and time-consuming operation, but triglyceride value above 400 (TG>400) always requires LDL measurement. Obtaining a fast LDL forecast by accurate prediction can be valuable to experts. However, if a high error margin exists, LDL prediction can be critical and unusable. Our objective is LDL value and level prediction with an error less than low total acceptable error rate (% TEa).

Keywords

• artificial intelligence
• ldl
• machine learning
• medical care
• prediction methods