Open AccessImproving Risk Identification of Adverse Outcomes in Chronic Heart Failure Using SMOTE+ENN and Machine Learning
Author(s) -
Ke Wang,
Jing Tian,
Chen Zheng,
Hong Yang,
Jia Ren,
Chenhao Li,
Qinghua Han,
Yanbo Zhang
Publication year - 2021
Publication title -
risk management and healthcare policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.828
H-Index - 22
ISSN - 1179-1594
DOI - 10.2147/rmhp.s310295
Subject(s) - brier score , medicine , receiver operating characteristic , support vector machine , adverse effect , logistic regression , random forest , confidence interval , identification (biology) , artificial intelligence , machine learning , computer science , botany , biology
This study sought to develop models with good identification for adverse outcomes in patients with heart failure (HF) and find strong factors that affect prognosis.