Dynamic data analysis and data mining for prediction of clinical stability.

Volume: 150, Pages: 590 - 4
Published: Jan 1, 2009
Abstract
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes according to the time they need to reach a stable state after coronary bypass surgery: less or more than nine hours. On the basis of five physiological variables different dynamic features were extracted. These sets of features served subsequently as inputs for a...
Paper Details
Title
Dynamic data analysis and data mining for prediction of clinical stability.
Published Date
Jan 1, 2009
Journal
Volume
150
Pages
590 - 4
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