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- W1987443343 abstract "Classification and regression tree has been useful in medical research to construct algorithms for disease diagnosis or prognostic prediction. Jin et al. 7 developed a robust and cost-saving tree (RACT) algorithm with application in classification of hip fracture risk after 5-year follow-up based on the data from the Study of Osteoporotic Fractures (SOF). Although conventional recursive partitioning algorithms have been well developed, they still have some limitations. Binary splits may generate a big tree with many layers, but trinary splits may produce too many nodes. In this paper, we propose a classification approach combining trinary splits and binary splits to generate a trinary–binary tree. A new non-inferiority test of entropy is used to select the binary or trinary splits. We apply the modified method in SOF to construct a trinary–binary classification rule for predicting risk of osteoporotic hip fracture. Our new classification tree has good statistical utility: it is statistically non-inferior ..." @default.
- W1987443343 created "2016-06-24" @default.
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- W1987443343 date "2013-06-01" @default.
- W1987443343 modified "2023-09-23" @default.
- W1987443343 title "Hip fracture prediction from a new classification algorithm based on recursive partitioning methods" @default.
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- W1987443343 doi "https://doi.org/10.1080/02664763.2013.785490" @default.
- W1987443343 hasPublicationYear "2013" @default.
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