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Deep Semi-Supervised Embedded Clustering (DSEC) for Stratification of Heart Failure Patients
In this work we apply deep semi-supervised embedded clustering to determine data-driven patient subgroups of heart failure from the electronic health records of 4, 487 heart failure and control patients.
Prediction of the onset of cardiovascular diseases from electronic health records using multi-task gated recurrent units
The proposed approach is compared to a standard clinical risk predictor (QRISK) and machine learning alternatives using 5-year data from a NHS Foundation Trust.
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