Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data
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Trained on a large, heterogeneous, real-world dataset, our CovRNN models showed high
prediction accuracy and transferability through consistently good performances on
multiple external datasets. Our results show the feasibility of a COVID-19 predictive
model that delivers high accuracy without the need for complex feature engineering.
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