Open AccessApplication of Machine Learning Algorithms to Predict Acute Kidney Injury in Elderly Orthopedic Postoperative Patients
Author(s) -
Qiuchong Chen,
Yixue Zhang,
Mengjun Zhang,
Ziying Li,
Jindong Liu
Publication year - 2022
Publication title -
clinical interventions in aging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.184
H-Index - 76
eISSN - 1178-1998
pISSN - 1176-9092
DOI - 10.2147/cia.s349978
Subject(s) - medicine , nomogram , acute kidney injury , logistic regression , receiver operating characteristic , brier score , orthopedic surgery , retrospective cohort study , algorithm , cohort , machine learning , emergency medicine , surgery , computer science
There has been a worldwide increment in acute kidney injury (AKI) incidence among elderly orthopedic operative patients. The AKI prediction model provides patients' early detection a possibility at risk of AKI; most of the AKI prediction models derive, however, from the cardiothoracic operation. The purpose of this study is to predict the risk of AKI in elderly patients after orthopedic surgery based on machine learning algorithm models.