Abstract：
The ReMIAMes project proposes a methodological framework to provide a reliable and reproducible measurement of the frequency of drug-drug interactions (DDI) when performed on real-world data. This framework relies on (i) a fine-grained and contextualized definition of DDIs, (ii) a shared minimum information model to select the appropriate data for the correct interpretation of potential DDIs, (iii) an ontology-based inference module able to handle missing data to classify prescription lines with potential DDIs, (iv) a report generator giving the value of the measurement and explanations when potential false positive are detected due to a lack of available data. All the tools developed are intended to be publicly shared under open license.
摘要：
ReMIAMes项目提出了一种方法框架，以在实际数据上进行时，提供可靠且可重复的药物相互作用（DDI）频率测量。这个框架依赖于(I)DDI的细粒度和上下文化定义，（ii）共享的最小信息模型，以选择正确解释潜在的DDI的适当数据，（iii）基于本体的推理模块，能够处理缺失的数据以对具有潜在DDI的处方行进行分类，（iv）报告生成器，当由于缺乏可用数据而检测到潜在的假阳性时，给出测量值和解释。所有开发的工具都打算在开放许可证下公开共享。
