A Relation Extraction Approach for Clinical Decision Support
This work addresses the need for more effective retrieval systems in clinical decision support, but it is incremental as it builds on existing relation extraction methods.
The paper tackled the problem of improving medical literature retrieval for clinical decision support by using semantic relations between concepts from medical documents, resulting in a sizable increase in precision for several topics, though with no impact on others.
In this paper, we investigate how semantic relations between concepts extracted from medical documents can be employed to improve the retrieval of medical literature. Semantic relations explicitly represent relatedness between concepts and carry high informative power that can be leveraged to improve the effectiveness of retrieval functionalities of clinical decision support systems. We present preliminary results and show how relations are able to provide a sizable increase of the precision for several topics, albeit having no impact on others. We then discuss some future directions to minimize the impact of negative results while maximizing the impact of good results.