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Textual extraction and classification for medical risk management: A new Risk Management Platform to manage undesired medical events

Abstract : In this paper, we propose a semi-automatic system to deal with the undesired events that may happen in the medical field. Based on algorithms of textual extraction and classifications, it performs a preprocessing of undesired events' declarations. The proposed system is currently running on different hospitals and some medical institutions in France. Computational study were made on a real-case instances and experimentations shows good results for the proposed approaches. © 2015 IEEE.
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https://hal-uphf.archives-ouvertes.fr/hal-03659144
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Submitted on : Wednesday, May 4, 2022 - 3:37:52 PM
Last modification on : Thursday, May 5, 2022 - 3:36:14 AM

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Salah Zidi, Julien Thibaut, Anis Mjirda, Fouad Maaloul. Textual extraction and classification for medical risk management: A new Risk Management Platform to manage undesired medical events. 4th International Conference on Advanced Logistics and Transport (ICALT), May 2015, Valenciennes, France. pp.235-239, ⟨10.1109/ICAdLT.2015.7136632⟩. ⟨hal-03659144⟩

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