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- W2893071716 abstract "In this work we focus on recently introduced “medical concept vectors” (MCV) extracted from electronic health records (EHR), explore in similar manner several methods useful for patient’s medical history events prediction and provide our own novel state-of-the-art method to solve this problem. We use MCVs to analyze publicly-available EHR de-identified data, with strong focus on fair comparison of several different models applied to patient’s death, heart failure and chronic liver diseases (cirrhosis and fibrosis) prediction tasks. We propose ontology-based regularization method that can be used to pre-train MCV embeddings. The approach we use to predict these diseases and conditions can be applied to solve other prediction tasks." @default.
- W2893071716 created "2018-10-05" @default.
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- W2893071716 date "2018-01-01" @default.
- W2893071716 modified "2023-10-02" @default.
- W2893071716 title "A Model-Free Comorbidities-Based Events Prediction in ICU Unit" @default.
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- W2893071716 doi "https://doi.org/10.1007/978-3-030-01204-5_10" @default.
- W2893071716 hasPublicationYear "2018" @default.
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