Prediction is at the heart of intensive care medicine, where physicians make use of their medical knowledge and all the patient-related data in order to foresee changes in the patient's condition, and administer the appropriate (preventive) treatments. An intensive care unit (ICU) is a very data-rich environment with several information sources, such as admission records, medical history, laboratory analyses of samples, medication and treatment records, and monitoring of vital signals. A Patient Data Management System (PDMS) (MetaVision®, iMD-Soft®, Boston, MA) was installed in our ICU starting in February 2006. This PDMS software automatically collects and integrates the data from the multiple information sources. One of the benefits of having all patient-related data in an integrated format is that it can be readily analyzed through the use of computational techniques in general and data mining in particular. These techniques make use of the information in large databases to automatically generate models that can be used for prediction (e.g. to predict a patient's probability of survival in ICU). In previous studies our research group has shown the high predictive performances than can be obtained with data mining models in the intensive care domain.