Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.

ABSTRACT: Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effects of a single metal with traditional methods. In this study, we analyzed the relationship between 13 urinary heavy metal concentrations and AMD using NHANES data between 2005 and 2008. We constructed and compared 11 machine learning models to identify the best model for predicting AMD risk. We further interpreted the models by Permutation Feature Importance (PFI), Partial Dependence Plot (PDP) analysis, and SHapley Additive exPlanations (SHAP) analysis. 216 AMD patients out of 2380 participants. The random forest (RF) model performed optimally

SUBMITTER: Gao X 

PROVIDER: S-EPMC11541880 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature