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Recherche d'information clinomique dans le Dossier Patient Informatisé : modélisation, implantation et évaluation.

Abstract : The aim of this thesis is part of the broad issue of information retrieval in Electronic Health Records (EHRs). The aspects tackled in this topic are numerous : on the one hand clinomics information retrieval within EHRs and secondly information retrieval within unstructured data from EHRs. As a first step, one of the objectives is to integrate in EHRs information beyond the scope of medicine to integrate data, information and knowledge from molecular biology ; omic data from genomics, proteomics or metabolomics. The integration of this type of data improves health information systems, their interoperability and the processing and exploitation of data for clinical purposes. An important challenge is to ensure the integration of heterogeneous data, through research on conceptual models of data, ontology and terminology servers, and semantic data warehouses. The integration of this data and their interpretation into a conceptual data model is an important challenge. Finally, it is important to integrate clinical research and fundamental research in order to ensure continuity of knowledge between research and clinical practice and to understand personalized medicine challenges. This thesis thus leads to the design and development of a generic model of omics data exploited in a prototype application for information retrieval and visualization in omic and clinical data within a sample of 2,000 patients. The second objective of this thesis is the multi-terminological indexing of medical documents through the development of the Extracting Concepts with Multiple Terminologies tool (ECMT). It uses terminologies embedded in the Health Terminology/Ontology Portal (HeTOP) to identify concepts in unstructured documents. From a document written by a human, and therefore potentially showing typing errors, spelling or grammar mistakes, the challenge is to identify concepts and thus structure the information contained in the text. In health information retrieval, indexing is of great interest for information retrieval in unstructured documents, such as reports and medical notes. This thesis proposes several methods and their evaluation along two axes : the indexing of medical texts using several terminologies and the processing of natural language in narrative medical notes.
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Submitted on : Thursday, January 18, 2018 - 4:46:09 PM
Last modification on : Wednesday, March 2, 2022 - 10:10:10 AM
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  • HAL Id : tel-01687719, version 1


Chloé Cabot. Recherche d'information clinomique dans le Dossier Patient Informatisé : modélisation, implantation et évaluation.. Traitement du texte et du document. Normandie Université, 2017. Français. ⟨NNT : 2017NORMR041⟩. ⟨tel-01687719⟩



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