  Radio pulsar surveys are producing many more pulsar candidates than can be
inspected by human experts in a practical length of time. Here we present a
technique to automatically identify credible pulsar candidates from pulsar
surveys using an artificial neural network. The technique has been applied to
candidates from a recent re-analysis of the Parkes multi-beam pulsar survey
resulting in the discovery of a previously unidentified pulsar.
