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Methods for analysing trauma injury
data with missing values, collected at a UK
hospital, are reported. One measure of injury
severity, the Glasgow coma score, which is
known to be associated with patient death, is
missing for 12% of patients in the dataset. In
order to include these 12% of patients in the
analysis, three different data imputation
techniques are used to estimate the missing
values. The imputed data sets are analysed by an
artificial neural network and logistic regression,
and their results compared in terms of sensitivity,
specificity, positive predictive value and negative
predictive value....
Nội dung trích xuất từ tài liệu:
Imputation Methods to Deal with Missing Values when Data Mining Trauma Injury Data
