Title: Machine learning techniques to examine large patient databases
Authors: Meyfroidt, Geert ×
Guiza Grandas, Fabian
Ramon, Jan
Bruynooghe, Maurice #
Issue Date: Mar-2009
Publisher: Bailliè€re Tindall
Series Title: Baillière's Best Practice & Research. Clinical Anaesthesiology vol:23 issue:1 pages:127-143
Abstract: Computerization in health care in general, and in the operating room (OR) and intensive care unit (ICU) in particular, is on the rise. This leads to large patient databases, with specific properties. Machine learning techniques are able to examine and to extract knowledge from large databases in an automatic way. Although the number of potential applications for these techniques in medicine is large, few medical doctors are familiar with their methodology, advantages and pitfalls. A general overview of machine learning techniques, with a more detailed discussion of some of these algorithms, is presented in this review
ISSN: 1521-6896
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Informatics Section
Unit for Clinical-Translational Research (-)
Laboratory of Intensive Care Medicine
× corresponding author
# (joint) last author

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