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Evaluation of Doc’EDS: A French Semantic Search Tool to Query Health Documents from A Clinical Data Warehouse
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Edité par CCSD -
Background: Unstructured data from electronic health record is a gold mine. Doc’EDS is a pre-screening tool based on textual and semantic analysis. The system provides an easy-to-use interface to search documents in French. The aim of this study is to present the tools and to provide a formal evaluation of its semantic features. Material & Methods: Doc’EDS is a search tool built on the top of the clinical data warehouse developed in the Rouen University Hospital. This tool is a multilevel search engine combining structured and unstructured data. It also provides basic analytics features and semantic utilities. A formal evaluation has been conducted to measure the implemented Natural Language Processing algorithms. Results: About 17,3 million of narrative documents are contained in this CDW. The formal evaluation has been conducted over 5,000 clinical concepts that were manually collected. Negation concepts detection F-measure was 0.89, hypothesis concept detection F-measure was 0.57. Conclusion: We hereby present Doc’EDS, a semantic search tool which deals with language subtleties to enhance an advanced full text search engine dedicated to French health documents. This tool is currently used on a daily basis to help researchers identifying patients thanks to unstructured data.
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