Open AccessPrediction of fatal adverse prognosis in patients with fever-related diseases based on machine learning: A retrospective study
Author(s) -
Chen Zhao,
Huitao Wu,
Hebin Che,
Yanan Song,
Yuzhuo Zhao,
Kaiyuan Li,
Hong-Ju Xiao,
Yi Zhai,
Xin Liu,
Hongxi Lu,
Tanshi Li
Publication year - 2020
Publication title -
chinese medical journal/chinese medical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 63
eISSN - 2542-5641
pISSN - 0366-6999
DOI - 10.1097/cm9.0000000000000675
Subject(s) - medicine , logistic regression , receiver operating characteristic , adaboost , retrospective cohort study , decision tree , random forest , odds ratio , adverse effect , machine learning , artificial intelligence , support vector machine , computer science
Fever is the most common chief complaint of emergency patients. Early identification of patients at an increasing risk of death may avert adverse outcomes. The aim of this study was to establish an early prediction model of fatal adverse prognosis of fever patients by extracting key indicators using big data technology.