Jia-Yu Liang

Cost Sensitive Interpretable Decision Making Framework for Diabetes Prediction

Machine learning in diabetes screening faces two challenges: data imbalance, leading to missed diagnosis of high-risk patients, and the lack of clinical interpretability of the "black box" model. This paper proposes an interpretable Light Gradient Boosting Machine (LightGBM) prediction architecture based on cost sensit...