Adverse drug reactions (ADRs) induced from high-order drug-drug interactions (DDIs) due to polypharmacy represent a significant public health problem. In this paper, we formally formulate the to-avoid and safe (with respect to ADRs) drug recommendation problems when multiple drugs have been taken simultaneously. We develop a joint model with a recommendation component and an ADR label prediction component to recommend for a prescription a set of to-avoid drugs that will induce ADRs if taken together with the prescription. We also develop real drug-drug interaction datasets and corresponding evaluation protocols. Our experimental results on real datasets demonstrate the strong performance of the joint model compared to other baseline methods.
Cite
@article{arxiv.1803.03185,
title = {Drug Recommendation toward Safe Polypharmacy},
author = {Wen-Hao Chiang and Li Shen and Lang Li and Xia Ning},
journal= {arXiv preprint arXiv:1803.03185},
year = {2018}
}