An intelligence risk detection framework using knowledge discovery to improve the efficiency of the decision making process in healthcare contexts: The case of paediatric congenital heart diseade

Moghimi, F, Seif Zadeh, H and Wickramasinghe, N 2011, 'An intelligence risk detection framework using knowledge discovery to improve the efficiency of the decision making process in healthcare contexts: The case of paediatric congenital heart diseade', in Guy Gable (ed.) PACIS 2011 - 15th Pacific Asia Conference on Information Systems: Quality Research in Pacific, Brisbane, Australia, 7-8 July 2011, pp. 1-10.


Document type: Conference Paper
Collection: Conference Papers

Title An intelligence risk detection framework using knowledge discovery to improve the efficiency of the decision making process in healthcare contexts: The case of paediatric congenital heart diseade
Author(s) Moghimi, F
Seif Zadeh, H
Wickramasinghe, N
Year 2011
Conference name PACIS
Conference location Brisbane, Australia
Conference dates 7-8 July 2011
Proceedings title PACIS 2011 - 15th Pacific Asia Conference on Information Systems: Quality Research in Pacific
Editor(s) Guy Gable
Publisher Queensland University of Technology
Place of publication Queesland, Australia
Start page 1
End page 10
Total pages 10
Abstract Healthcare professionals, especially surgeons must make complex decisions with far reaching consequences and associated risks. As has been shown in other industries, the ability to drill down into pertinent data to explore knowledge behind the data greatly facilitates superior, informed decisions to ensue. This proposal proffers an Intelligent Risk Detection (IRD) Model using data mining techniques followed by Knowledge Discovery in order to detect the dominant risk factors across a complex surgical decision making process and thereby to predict the surgery results and hence support superior decision making. To illustrate the benefits of this model, the case of the Congenital Heart Disease (CHD) is presented1.
Subjects Health Informatics
Keyword(s) Knowledge Discovery
Data Mining
Risk detection
Decision making
Congenital Heart Disease (CHD)
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