Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies

ArXi:2605.22243v1 Announce Type: cross Predictive modelling is important for health data analysis and data-driven clinical decision-making. However, predictive studies are challenging to design optimally by hand when tens or even hundreds of features require selection, transformation, or interaction modelling. While complex machine learning models offer high performance, their "black-box" nature limits the clinical trust, transparency, and interpretability required for decision-making.