Many patients with chronic diseases resort to multiple medications to relieve
various symptoms, which raises concerns about the safety of multiple medication
use, as severe drug-drug antagonism can lead to serious adverse effects or even
death. This paper presents a Decision Support System, called DSSDDI, based on
drug-drug interactions to support doctors prescribing decisions. DSSDDI
contains three modules, Drug-Drug Interaction (DDI) module, Medical Decision
(MD) module and Medical Support (MS) module. The DDI module learns safer and
more effective drug representations from the drug-drug interactions. To capture
the potential causal relationship between DDI and medication use, the MD module
considers the representations of patients and drugs as context, DDI and
patients' similarity as treatment, and medication use as outcome to construct
counterfactual links for the representation learning. Furthermore, the MS
module provides drug candidates to doctors with explanations. Experiments on
the chronic data collected from the Hong Kong Chronic Disease Study Project and
a public diagnostic data MIMIC-III demonstrate that DSSDDI can be a reliable
reference for doctors in terms of safety and efficiency of clinical diagnosis,
with significant improvements compared to baseline methods.

该论文提出了一个基于药物相互作用的决策支持系统，可提供更安全、更有效的药物处理方案，包括药物相互作用模块，医学决策模块和医疗支持模块，实验证明此系统可用于慢性疾病的临床诊断。