Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease
出版年份 2018 全文链接
标题
Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease
作者
关键词
Myocardial infarction, Decision trees, Machine learning, Angina, Forests, Cholesterol, Coronary artery bypass grafting, Coronary heart disease
出版物
PLoS One
Volume 13, Issue 8, Pages e0202344
出版商
Public Library of Science (PLoS)
发表日期
2018-09-01
DOI
10.1371/journal.pone.0202344
参考文献
相关参考文献
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