Machine Learning Analysis of Nutrient Associations with Peripheral Arterial Disease: Insights from NHANES 1999-2004.
Journal:
Annals of vascular surgery
PMID:
39892831
Abstract
BACKGROUND: Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis, affecting over 200 million people worldwide. The incidence of PAD is increasing due to the aging population. Common risk factors include smoking, diabetes, and hyperlipidemia, but its exact pathogenesis remains unclear. Nutritional intake is associated with the onset and progression of PAD, although relevant studies remain limited. Some studies suggest that certain nutritional elements may influence the development of PAD. This study aims to explore the relationship between nutrition and PAD using machine learning techniques. Unlike traditional statistical methods, machine learning can effectively capture complex, nonlinear relationships, providing a more comprehensive analysis of PAD risk factor.