Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases
This work addresses document matching and information retrieval for French clinical cases, but it is incremental as it applies existing methods to a specific dataset.
The paper tackled semantic similarity between clinical cases and discussions and information extraction from French clinical texts, reporting very encouraging accuracy results for the extraction system.
This paper reports on Qwant Research contribution to tasks 2 and 3 of the DEFT 2019's challenge, focusing on French clinical cases analysis. Task 2 is a task on semantic similarity between clinical cases and discussions. For this task, we propose an approach based on language models and evaluate the impact on the results of different preprocessings and matching techniques. For task 3, we have developed an information extraction system yielding very encouraging results accuracy-wise. We have experimented two different approaches, one based on the exclusive use of neural networks, the other based on a linguistic analysis.