Mining data from intensive care patients

In this paper we describe the application of data mining methods for predicting the evolution of patients in an intensive care unit. We discuss the importance of such methods for health care and other application domains of engineering. We argue that this problem is an important but challenging one for the current state of the art data mining methods and explain what improvements on current methods would be useful. We present a promising study on a preliminary data set that demonstrates some of the possibilities in this area. Key words: Intensive care, dynamic systems

• Type: Journal
• Year: 2007
• Where: AEI
• Authors: Jan Ramon, Daan Fierens, Fabián Güiza, Geert Meyfroidt, Hendrik Blockeel, Maurice Bruynooghe, Greet Vanden Berghe
• Keywords: AEI 2007, Data Mining Methods, Intensive Care, Intensive Care Unit