Afficher la pageAnciennes révisionsLiens de retourExporter en PDFExportation ODTHaut de page Cette page est en lecture seule. Vous pouvez afficher le texte source, mais ne pourrez pas le modifier. Contactez votre administrateur si vous pensez qu'il s'agit d'une erreur. ====== PREDHIC: Predicting heart failure readmission and mortality using natural language processing ====== While natural language processing performance has increased in recent years from a technical point of view, it is important to investigate how it contributes to a decision-making task that helps a specialist based upon information found in text. In that context, the specialized domain limits the availability of in-domain training data and emphasizes the importance of terminology and a priori knowledge; and typically not only text, but also structured data need to be taken into account. PREDHIC investigates associated research directions in state-of-the-art neural text representation and classification methods, and evaluates their impact on a real task, with real data, with a multicentric design: the assessment of the risk of readmission and mortality of heart failure patients after hospital discharge, a question of high clinical interest. It associates NLP specialists from two computer science teams to medical information and heart failure specialists from two hospitals. start.txt Dernière modification : 2021/09/15 00:45de pz S'identifier