Artificial intelligence for precision obesity phenotyping and cardiometabolic risk stratification: A critical narrative review

Background

Body mass index is a widely used obesity metric but does not adequately capture adiposity distribution, metabolic dysfunction, or individual cardiometabolic risk, leading to misclassification of conditions such as normal-weight obesity, metabolically healthy obesity, and excess visceral fat. With the rising global burden of obesity and related cardiovascular and metabolic diseases, more precise and biologically informative risk-stratification approaches are urgently needed.