Before revision:  Finally, we demonstrate that while the number of drugs and co-administrations help predict a patient's number of DDI (R^2=.413), they are not sufficient to flag these patients accurately, which we achieve by training classifiers with additional data (MCC= .83,F1 = .72 ).
After revision:  Finally, we demonstrate that machine learning classifiers accurately predict patients likely to be administered DDI given their history of prescribed drugs, gender, and age (MCC= .83,F1 = .72 ).