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

Heat Map, a Visual Tool for Comparative Analytics.

[BibT_eX]

[DOI]

Jamie C. Palumbo

Randall C. Wetzel

Gerardo Soto-Campos

Proceedings of the AMIA 2018, 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

Marked Point Process for Severity of Illness Assessment.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Health Care Conference, 2017

The Dependence of Machine Learning on Electronic Medical Record Quality.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2017, 2017

2016

Learning to Diagnose with LSTM Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series.

[BibT_eX]

[DOI]

Zachary C. Lipton

David C. Kale

Randall C. Wetzel

Proceedings of the 1st Machine Learning in Health Care, 2016

DRTED: Deep learning Recommendation of Treatment from Electronic Data.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2016, 2016

2015

Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks.

[BibT_eX]

[DOI]

Zachary Chase Lipton

David C. Kale

Randall C. Wetzel

CoRR, 2015

Causal Phenotype Discovery via Deep Networks.

[BibT_eX]

[DOI]

David C. Kale

Zhengping Che

Mohammad Taha Bahadori

Wenzhe Li

Yan Liu

Randall C. Wetzel

Proceedings of the AMIA 2015, 2015

2014

An Examination of Multivariate Time Series Hashing with Applications to Health Care.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

2012

Unsupervised pattern discovery in electronic health care data using probabilistic clustering models.

[BibT_eX]

[DOI]

Proceedings of the ACM International Health Informatics Symposium, 2012

2011

An informatics architecture for the Virtual Pediatric Intensive Care Unit.

[BibT_eX]

[DOI]

Paul Veeravatanayothin

Amy Braverman

Cameron Goodale

Randall C. Wetzel

Proceedings of the 24th IEEE International Symposium on Computer-Based Medical Systems, 2011

Randall C. Wetzel

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