A Coruña, España
Often, a study or research process requires the analysis of large volumes of information in the form of unstructured text. This task consumes a large amount of time and resources of the human experts in charge of it. For this reason, there is great interest in developing automatic systems to support these activities by applying Text Mining techniques. A key task in this type of process is Entity Recognition: extracting the entities of interest contained in a text and classifying them into pre-established categories. Thework presented here is part of the GRALENIA project, which seeks to improve antimicrobial resistance data management in the hospital setting. The main goal of our work is the development of an entity recognizer prototype for the identification and labeling of indicators of interest present in clinical reports
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