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.
@article{arxiv.1907.05790,
title = {Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases},
author = {Estelle Maudet and Oralie Cattan and Maureen de Seyssel and Christophe Servan},
journal= {arXiv preprint arXiv:1907.05790},
year = {2019}
}
Comments
Article accepted at the workshop DEfi fouille de Texte (DEFT 2019). Article in French