Be the first to like this
Semantic MEDLINE applies automatic summarization techniques to manage the semantic predications extracted from the biomedical literature by SemRep. It does so by selecting salient predications based on several criteria. In this study, we investigated a new technique to automatically summarize SemRep predications. Our technique leverages hierarchical relations from the UMLS Metathesaurus for aggregating the semantic predications. We also generated new inferences from the aggregated semantic predications. Several quantitative measures are dened to evaluate the system. We applied our method to summarize medications used to treat diseases and also adverse drug events reported in the biomedical literature. Our preliminary experimental results are promising in terms of summarization rate. They also indicate that less than half of the newly generated inferences correspond to existing relations. Further work is needed to evaluate the rest of the inferences.