Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea.

Sun-Min ParkChaeyeon KimXuangao Wu

Published in: Diagnostics (Basel, Switzerland) (2022)

The liver function, regular pulse checking, and seasonal variation in addition to metabolic syndrome components should be considered to predict insulin resistance in Koreans aged over 40 years.

Keyphrases

insulin resistance
metabolic syndrome
machine learning
high fat diet
adipose tissue
polycystic ovary syndrome
skeletal muscle
blood pressure
uric acid
type diabetes
artificial intelligence
high fat diet induced
cardiovascular risk factors
big data
deep learning
glycemic control
cardiovascular disease