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Predicting readmission risk from doctors' notes

Abstract

We develop a model using deep learning techniques and natural language processing on unstructured text from medical records to predict hospital-wide 3030-day unplanned readmission, with c-statistic .70.70. Our model is constructed to allow physicians to interpret the significant features for prediction.

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