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Project

Clinical prediction models in intensive care.

Intensive care medicine allows patients to survive lethal insults. Physicians in this domain use their medical knowledge and patient-related data to foresee changes in the patient's health-state, and administer treatments. Intensive Care Units (ICUs) are very data rich environments, and recently many have implemented software that automatically collects and integrates the data from the multiple information sources into a Patient Data Management System (PDMS). Having all patient data in an integrated format allows it to be analyzed with computational techniques such as data mining. Data mining can be used to develop clinical models that have high predictive performance, as was shown in previous work by our research group. In this project we will use these techniques to build clinical models of interest in the intensive care setting.
Date:1 Jan 2011 →  31 Dec 2014
Keywords:Intensive care medicine, Data mining, Clinical predictive models
Disciplines:Anaesthesiology, Intensive care and emergency medicine