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Fouille de texte et extraction d'informations dans les données cliniques

Clément Dalloux 1 
1 LinkMedia - Creating and exploiting explicit links between multimedia fragments
Inria Rennes – Bretagne Atlantique , IRISA-D6 - MEDIA ET INTERACTIONS
Abstract : With the introduction of clinical data warehouses, more and more health data are available for research purposes. While a significant part of these data exist in structured form, much of the information contained in electronic health records is available in free text form that can be used for many tasks. In this manuscript, two tasks are explored: the multi-label classification of clinical texts and the detection of negation and uncertainty. The first is studied in cooperation with the Rennes University Hospital, owner of the clinical texts that we use, while, for the second, we use publicly available biomedical texts that we annotate and release free of charge. In order to solve these tasks, we propose several approaches based mainly on deep learning algorithms, used in supervised and unsupervised learning situations.
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Submitted on : Wednesday, March 31, 2021 - 3:05:38 PM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM


Version validated by the jury (STAR)


  • HAL Id : tel-03081563, version 2


Clément Dalloux. Fouille de texte et extraction d'informations dans les données cliniques. Base de données [cs.DB]. Université Rennes 1, 2020. Français. ⟨NNT : 2020REN1S050⟩. ⟨tel-03081563v2⟩



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