A Comparison of Data Mining Methods and Logistic Regression to Determine Factors Associated with Death Following Injury

Kay Penny*, Thomas Chesney

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

Abstract

A comparison of techniques for analysing trauma injury data collected over ten years at a hospital trauma unit in the U.K. is reported. The analysis includes a comparison of four data mining techniques to determine factors associated with death following injury. The techniques include a classification and regression tree algorithm, a classification algorithm, a neural network and logistic regression. As well as techniques within the data mining framework, conventional logistic regression modelling is also included for comparison. Results are compared in terms of sensitivity, specificity, positive predictive value and negative predictive value.
Original languageEnglish
Title of host publicationData Analysis, Classification and the Forward Search
Subtitle of host publicationProceedings of the meeting of CLADAG 2005
EditorsS Zani, A Cerioli, M Riani, M Vichi
Place of PublicationHeidelberg
PublisherSpringer-Verlag Berlin Heidelberg
Pages417-423
ISBN (Print)978-3-540-35977-7
DOIs
Publication statusPublished - 2006

Publication series

NameStudies in Classification, Data Analysis, and Knowledge Organization.
PublisherSpringer, Berlin

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