XGBoost for Interpretable Alzheimer’s Decision Support

Despite their necessity in directing patient care worldwide, simple and accurate diagnostic tools for early Alzheimer’s disease (AD) do not exist. To support healthcare decisionmaking and planning, this research leverages large, multi-site accessible data and state-of-the-art supervised machine learning (XGBoost) to enable rapid, accurate, low-cost, accessible, non-invasive, interpretable, and early clinical evaluation of AD. Machine learning …