Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity

This data-driven study identified a novel classification strategy to identify subtypes of the middle-aged and elderly Chinese with general obesity and central obesity and classify their adiposity and cardio-metabolic profiles. With clinically accessible metrics, this approach could inform precise risk stratification by revealing subtype-specific heterogeneity during initial assessments.