Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke

In conclusion, the authors developed a new predictive model using SVM regression starting from common inflammatory biomarkers and other ratio markers. The main efforts of our model have been accomplished in regard to the evidence that the type of stroke has not shown itself to be a critical input variable to predict the discharge data, furthermore, among the four selected indicators, Barthel at T1 is the less predictable (MADP > 80%), while it is possible to predict T1 Cognitive FIM with an MADP less than 18%.