Predicting risk for adverse health events using random forest

DOI10.1080/02664763.2017.1414166OpenAlexW2781081926MaRDI QIDQ5036398

Elizabeth W. Paxton, Juanjuan Fan, Guy Cafri, Luo Li

Publication date: 23 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2017.1414166

zbMATH Keywords

survivalmachine learningnonparametricrandom forestcompeting risktotal knee replacement

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Related Items (1)

Variable selection and importance in presence of high collinearity: an application to the prediction of lean body mass from multi-frequency bioelectrical impedance

Uses Software

• randomSurvivalForest
• ElemStatLearn

Cites Work

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• Bagging predictors
• Random survival forests
• A class of k-sample tests for comparing the cumulative incidence of a competing risk
• The effect of splitting on random forests
• High-Dimensional Variable Selection for Survival Data
• Extremely randomized trees
• Random forests

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