Using convolutional neural networks to identify patient safety incident reports by type and severity.

Journal: Journal of the American Medical Informatics Association : JAMIA

Published Date: Dec 1, 2019

Abstract

OBJECTIVE: To evaluate the feasibility of a convolutional neural network (CNN) with word embedding to identify the type and severity of patient safety incident reports.

Authors

Ying Wang

Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
Enrico Coiera

1Australian Institute of Health Innovation, Macquarie University, Level 6 75 Talavera Rd, Sydney, NSW 2109 Australia.
Farah Magrabi

Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Australia.

Keywords

Classification Feasibility Studies Humans Medical Errors Neural Networks, Computer Patient Safety Risk Management Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (31730700)

Using convolutional neural networks to identify patient safety incident reports by type and severity.

Abstract

Authors

Keywords

External Resources

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