Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

Journal: Methods of information in medicine

Published Date: Aug 16, 2017

Abstract

OBJECTIVE: To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements.

Authors

Xingyu Zhang

Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA.
Joyce Kim
Rachel E Patzer

Surgical Outcomes and Quality Improvement Center (SOQIC), Department of Surgery, Indiana School of Medicine, Indianapolis, IN; Center for Health Services Research, Regienstrief Institute, Indianapolis, IN.
Stephen R Pitts
Aaron Patzer
Justin D Schrager

Keywords

Adolescent Adult Aged Emergency Service, Hospital Female Hospitalization Humans Male Middle Aged Models, Theoretical Natural Language Processing Neural Networks, Computer ROC Curve Vital Signs Young Adult

External Resources

View on PubMed Access via DOI PubMed (28816338)

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

Abstract

Authors

Keywords

External Resources

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