Enhancing Drug-Drug Interaction Extraction from Texts by Molecular Structure Information
Table 4: Classification of DDIs in texts by molecular structure-based DDI classification model
['Methods', 'P', 'R', 'F', 'Acc. (%)']
Finally, we applied the molecular-based DDI classification model trained on DrugBank to the DDIExtraction 2013 task data set. Since the DrugBank has no detailed labels, we mapped all four types of interactions to positive interactions and evaluated the classification performance. This might be because the interactions of drugs are not always mentioned in texts even if the drugs can interact with each other and because hedged DDI mentions are annotated as DDIs in the text data set. We also trained the DDI extraction model only with molecular information by replacing hall with hm, but the F-scores were quite low (< 5%). These results show that we cannot predict textual relations only with molecular information.