Machine Learning-Based Identification of Key Predictors of Estimated Glomerular Filtration Rate in Older Taiwanese Women

Abstract

Background : Estimated glomerular filtration rate (GFR) is widely used to assess kidney function but is primarily derived from serum creatinine, which is affected by age, sex, muscle mass, nutrition, inflammation, and fluid status. We aimed to identify key predictors of eGFR using machine learning.

The paper