Nutrients, Vol. 17, Pages 3368: Interpretable Machine Learning Identification of Dietary and Metabolic Factors for Metabolic Syndrome in Southern China: A Cross-Sectional Study
Nutrients, Vol. 17, Pages 3368: Interpretable Machine Learning Identification of Dietary and Metabolic Factors for Metabolic Syndrome in Southern China: A Cross-Sectional Study Nutrients doi: 10.3390/nu17213368 Authors: Xi Meng Yiting Fang Shuaijing Zhang Panpan Huang Jian Wen Jiewen Peng Xingfen Yang Guiyuan Ji Wei Wu Background: Metabolic syndrome (MetS) is a rising public health concern […]
