LEVERAGING MACHINE LEARNING METHODS IN PREDICTING AND ANALYZING THE ASSOCIATION BETWEEN DIETARY INFLAMMATORY INDEX AND ALOPECIA

This study explores the link between the dietary inflammatory index (DII) and alopecia areata (AA) using machine learning models such as K-Nearest Neighbors, Logistic Regression, and Random Forest. It was found that higher DII scores, which reflect a more inflammatory diet, are significantly associated with a greater risk and severity of AA. The Random Forest model demonstrated the highest accuracy at 98.77%. These results suggest that inflammatory dietary patterns may affect AA, indicating possible dietary intervention strategies for managing the condition.