# A Relation Extraction Approach for Clinical Decision Support

arXiv: https://arxiv.org/abs/1905.01257 · HTML: https://mlsanity.com/paper/1905.01257/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 May 2019.

## Built on by (most cited first, 1 of 1)

- [A Study on Building Efficient Zero-Shot Relation Extraction Models](https://mlsanity.com/paper/2603.01266/) (2026)

## Abstract (arXiv)

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.