AI-driven prediction of insulin resistance in non-diabetic populations using minimal invasive tests: comparing models and criteria

This study successfully developed a minimally invasive insulin resistance prediction model that relies solely on fasting blood glucose. The AI-driven models demonstrated robust performance across multiple insulin resistance assessment indicators, particularly in predicting the METS-IR index. These findings highlight the significant potential of AI in enhancing early detection and monitoring of insulin resistance in non-diabetic populations, thereby improving health monitoring strategies.