Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning
Abstract Background Discovering potential drug-drug interactions (DDIs) is a long-standing challenge in clinical treatments and drug developments.Recently, deep learning techniques have been developed for DDI prediction.However, they generally require a huge number of samples, while known DDIs are rare.Methods In this work, we present KnowDDI, a gr