Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances

Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances

We derived machine learning models utilizing features generated by natural language processing (NLP) of free-text data from an ambulance services provider to identify fall cases. The data comprised samples of electronic patient care records care records (ePCRs) from St John Western Australia (WA), t...

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Bibliographic Details
Main Authors: Tohira, Hideo, Finn, Judith, Ball, Stephen, Brink, D., Buzzacott, Peter
Format: Journal Article
Language:English
Published: 2021
Subjects:
Emergency medical services
random forest
support vector machine
text frequency-inverse document frequency
Online Access:http://hdl.handle.net/20.500.11937/87826

Internet

http://hdl.handle.net/20.500.11937/87826

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