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Neural Network Prediction of ICU Length of Stay Following Cardiac Surgery Based on Pre-Incision Variables

https://doi.org/10.1371/journal.pone.0145395
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Use of a Neural Network as a Predictive Instrument for Length of Stay in the Intensive Care Unit Following Cardiac Surgery
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The use of artificial neural networks to stratify the length of stay of cardiac patients based on preoperative and initial postoperative factors
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An original model to predict Intensive Care Unit length-of stay after cardiac surgery in a competing risk framework
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Optimal Linear Combinations of Neural Networks
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An artificial neural network ensemble to predict disposition and length of stay in children presenting with bronchiolitis
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A Novel Neural-Network Model for Deriving Standard 12-Lead ECGs From Serial Three-Lead ECGs: Application to Self-Care
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Predicting adverse outcomes of cardiac surgery with the application of artificial neural networks
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Predictive Inference
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Artificial neural networks in medical diagnosis
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Application of artificial neural networks for versatile preprocessing of electrocardiogram recordings
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Artificial neural network for normal, hypertensive, and preeclamptic pregnancy classification using maternal heart rate variability indexes
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Using an Artificial Neural Networks (ANNs) Model for Prediction of Intensive Care Unit (ICU) Outcome and Length of Stay at Hospital in Traumatic Patients

What points at this work

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Additional file 1 of Predicting the risk and timing of major mood disorder in offspring of bipolar parents: exploring the utility of a neural network approach
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