Identifying diagnostic indicators for type 2 diabetes mellitus from physical examination using interpretable machine learning approach

ConclusionThis work utilized the interpretable WDD-based algorithms to construct T2DM diagnostic models based on physical examination indicators. By modeling data grouped by age and sex, we identified several predictive markers related to age and sex, uncovering characteristic differences among various groups of T2DM patients.
Source: Frontiers in Endocrinology - Category: Endocrinology Source Type: research