Deep learning detects and visualizes bleeding events in electronic health records

BACKGROUND: Bleeding is associated with a significantly increased morbidity and mortality. Bleeding events are often described in the unstructured text of electronic health records, which makes them difficult to identify by manual inspection. OBJECTIVES: To develop a deep learning model that detects...

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發表在:Res Pract Thromb Haemost
Main Authors: Pedersen, Jannik S., Laursen, Martin S., Rajeeth Savarimuthu, Thiusius, Hansen, Rasmus Søgaard, Alnor, Anne Bryde, Bjerre, Kristian Voss, Kjær, Ina Mathilde, Gils, Charlotte, Thorsen, Anne‐Sofie Faarvang, Andersen, Eline Sandvig, Nielsen, Cathrine Brødsgaard, Andersen, Lou‐Ann Christensen, Just, Søren Andreas, Vinholt, Pernille Just
格式: Artigo
語言:Inglês
出版: John Wiley and Sons Inc. 2021
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Original Articles
在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC8114029/
https://ncbi.nlm.nih.gov/pubmed/34013150
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/rth2.12505
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