What patient information allows us to make accurate predictions of outcome?
D. R. Lovell, C. R. Dance, M. Niranjan, R. W. Prager, and K. J. Dalton
Only some of the information contained in a medical record
will be useful to the prediction of patient outcome. We describe a
novel method for selecting those outcome predictors which allow us to
reliably discriminate between adverse and benign end results. Using
the area under the receiver operating characteristic as a
non-parametric measure of discrimination, we show how to calculate the
maximum discrimination attainable with a given set of discrete valued
features. This upper limit forms the basis of our feature selection
algorithm. We use the algorithm to select features (from maternity
records) relevant to the prediction of failure to progress in
labour. The results of this analysis motivate investigation of those
predictors of failure to progress relevant to parous and nulliparous
sub-populations.
Keywords: Feature selection, risk prediction, pregnancy