Classification algorithms for hip fracture prediction based on recursive partitioning methods.
This article presents 2 modifications to the classification and regression tree. The authors improved the robustness of a split in the test sample approach and developed a cost-saving classification algorithm by selecting noninferior to the optimum splits from variables with lower cost or being used...
| Publicado en: | Medical Decision Making Vol. 24; no. 4; pp. 386 - 399 |
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| Autores principales: | , , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
Jul/Aug2004
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=106627270&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106627270 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0272989X DKI jtl: Medical Decision Making issn: 0272989X maglogo: Y pubinfo: dt: Jul/Aug2004 vid: 24 iid: 4 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 106627270 106627270 2005078394 10.1177/0272989x04267009 NLM15271277 106627270 ppf: 386 ppct: 13 formats: tig: atl: Classification algorithms for hip fracture prediction based on recursive partitioning methods. aug: au: Jin H Lu Y Harris ST Black DM Stone K Hochberg MC Genant HK affil: Department of Radiology, University of California, San Francisco sug: subj: Hip Fractures Classification Hip Fractures Economics Classification Algorithms Aged Bone Density Cost Benefit Analysis Descriptive Statistics Female P-Value Predictive Value of Tests Sensitivity and Specificity Funding Source Human Aged: 65+ years Female ab: This article presents 2 modifications to the classification and regression tree. The authors improved the robustness of a split in the test sample approach and developed a cost-saving classification algorithm by selecting noninferior to the optimum splits from variables with lower cost or being used in parent splits. The new algorithm was illustrated by 43 predictive variables for 5-year hip fracture previously documented in the Study of Osteoporotic Fractures. The authors generated the robust optimum classification rule without consideration of classification variable costs and then generated an alternative cost-saving rule with equivalent diagnostic utility. A 6-fold cross-validation study proved that the cost-saving alternative classification is statistically noninferior to the optimal one. Their modified classification and regression tree algorithm can be useful in clinical applications. A dual X-ray absorptiometry hip scan and information from clinical examinations can identify subjects with elevated 5-year hip fracture risk without loss of efficiency to more costly and complicated algorithms. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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