Disability Prediction in Multiple Sclerosis using Ensemble of Machine Learning Models and DTI Brain Connectivity

The Expanded Disability Status Scale (EDSS) monitors physical impairment in Multiple Sclerosis (MS). A Staking Ensemble model composed of 4 ML "boosting" models was used to predict EDSS using both white matter (WM) fiber-bundles and structural connectome data. This model provided excellent prediction results with an RMSE of 0.92 to 1.08. A counterfactual model was added to highlight the most important WM links and fiber-bundles in the prediction process. The accordance of the findings obtained with both data types confirmed the clinical interest of such methods for disability prediction using DTI data.