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Effectiveness of LSTMs in Predicting Congestive Heart Failure Onset
In this paper we present a Recurrent neural networks (RNN) based architecture that achieves an AUCROC of 0. 9147 for predicting the onset of Congestive Heart Failure (CHF) 15 months in advance using a 12-month observation window on a large cohort of 216, 394 patients.
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