Open AccessPredicting 72-hour and 9-day return to the emergency department using machine learning
Author(s) -
Woo Suk Hong,
Adrian D. Haimovich,
Richard A. Taylor
Publication year - 2019
Publication title -
jamia open
Language(s) - English
Resource type - Journals
ISSN - 2574-2531
DOI - 10.1093/jamiaopen/ooz019
Subject(s) - emergency department , expansive , electronic health record , boosting (machine learning) , names of the days of the week , gradient boosting , time of day , computer science , medical emergency , artificial intelligence , medicine , health care , nursing , economics , random forest , zoology , linguistics , philosophy , materials science , compressive strength , composite material , biology , economic growth
To predict 72-h and 9-day emergency department (ED) return by using gradient boosting on an expansive set of clinical variables from the electronic health record.
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