Open AccessElectronic Medical Record–Based Machine Learning Approach to Predict the Risk of 30-Day Adverse Cardiac Events After Invasive Coronary Treatment: Machine Learning Model Development and Validation
Author(s) -
Osung Kwon,
Wonjun Na,
Hee-Jun Kang,
Tae Joon Jun,
Jihoon Kweon,
GyungMin Park,
YongHyun Cho,
Cinyoung Hur,
Jung-woo Chae,
DoYoon Kang,
Pil Hyung Lee,
JungMin Ahn,
DukWoo Park,
Soo–Jin Kang,
Cheol Whan Lee,
Seung-Whan Lee,
Seong-Wook Park,
SeungJung Park,
Dong Hyun Yang,
YoungHak Kim
Publication year - 2022
Publication title -
jmir medical informatics
Language(s) - English
Resource type - Journals
ISSN - 2291-9694
DOI - 10.2196/26801
Subject(s) - medicine , receiver operating characteristic , brier score , random forest , gradient boosting , machine learning , logistic regression , percutaneous coronary intervention , adverse effect , artificial intelligence , medical record , emergency medicine , computer science , myocardial infarction