Open AccessDevelopment of a random forest model for hypotension prediction after anesthesia induction for cardiac surgery
Author(s) -
Xuan-Fa Li,
YongZhen Huang,
Jing-Ying Tang,
Ruichen Li,
Xiaoqi Wang
Publication year - 2021
Publication title -
world journal of clinical cases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.368
H-Index - 10
ISSN - 2307-8960
DOI - 10.12998/wjcc.v9.i29.8729
Subject(s) - medicine , adverse effect , anesthesia , blood pressure , receiver operating characteristic , random forest , machine learning , computer science
Hypotension after the induction of anesthesia is known to be associated with various adverse events. The involvement of a series of factors makes the prediction of hypotension during anesthesia quite challenging.