Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model
Open Access
- 25 October 2011
- journal article
- research article
- Published by Springer Science and Business Media LLC in BMC Medical Informatics and Decision Making
- Vol. 11 (1), 64
- https://doi.org/10.1186/1472-6947-11-64
Abstract
The intensive care unit (ICU) length of stay (LOS) of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for ICU discharge after non-emergency cardiac surgery, by analyzing the first 4 hours of data in the computerized medical record of these patients with Gaussian processes (GP), a machine learning technique.Keywords
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