Adverse drug reaction prediction and feature importance mining based on SIDER dataset

Abstract

Adverse Drug Reaction (ADR) refer to harmful and irrelevant reactions that occur when normal dosage drugs are used to prevent, diagnose, treat diseases or regulate physiological functions. This definition excludes reactions caused by intentional or accidental overdose and inappropriate medication. In this paper, several models were measured and compared. The results demonstrated that base learners such as LR, SVM, RF, Adaboost, XGBoost may perform exceptionally well in some specific situations. On the other hand, if the precision of the outputs is emphasized, applying Stacking or even Multi-layer Stacking will be the most efficient tool.