Predicting High-Flow Nasal Cannula Failure in an ICU Using a Recurrent Neural Network with Transfer Learning and Input Data Perseveration: A Retrospective Analysis.

[BibT_eX]

[DOI]

George A. Pappy

Melissa D. Aczon

Randall C. Wetzel

David R. Ledbetter

CoRR, 2021

Improving Recurrent Neural Network Responsiveness to Acute Clinical Events.

[BibT_eX]

[DOI]

IEEE Access, 2021

2020

The impact of extraneous features on the performance of recurrent neural network models in clinical tasks.

[BibT_eX]

[DOI]

J. Biomed. Informatics, 2020

2019

Interpreting a Recurrent Neural Network Model for ICU Mortality Using Learned Binary Masks.

[BibT_eX]

[DOI]

CoRR, 2019

The Impact of Extraneous Variables on the Performance of Recurrent Neural Network Models in Clinical Tasks.

[BibT_eX]

[DOI]

CoRR, 2019

Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unit.

[BibT_eX]

[DOI]

J. Am. Medical Informatics Assoc., 2018

2017

Predicting Individual Physiologically Acceptable States for Discharge from a Pediatric Intensive Care Unit.

[BibT_eX]

[DOI]

CoRR, 2017

Dynamic Mortality Risk Predictions in Pediatric Critical Care Using Recurrent Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2017

The Dependence of Machine Learning on Electronic Medical Record Quality.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2017, 2017

2016

DRTED: Deep learning Recommendation of Treatment from Electronic Data.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2016, 2016

David R. Ledbetter

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