Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/9544
Title: Risk assessment for primary coronary heart disease event using dynamic bayesian networks
Authors: Orphanou, Kalia 
Stassopoulou, Athena 
Keravnou-Papailiou, Elpida 
Keywords: Dynamic Bayesian networks;Primary coronary heart disease;Risk assessment;Temporal abstraction;Temporal reasoning
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: 1-Jan-2015
Publisher: Springer Verlag
Source: 15th Conference on Artificial Intelligence in Medicine, 2015, Pavia, Italy
metadata.dc.doi: 10.1007/978-3-319-19551-3_20
Abstract: Coronary heart disease (CHD) is the leading cause of mortality worldwide. Primary prevention ofCHDdenotes limiting a firstCHDevent in individuals who have not been formally diagnosed with the disease. This paper demonstrates how the integration of a Dynamic Bayesian network (DBN) and temporal abstractions (TAs) can be used for assessing the risk of a primaryCHDevent. More specifically, we introduce basic TAs into the DBN nodes and apply the extended model to a longitudinal CHDdataset for risk assesment. The obtained results demonstrate the effectiveness of our proposed approach.
URI: http://ktisis.cut.ac.cy/handle/10488/9544
ISBN: 978-331919550-6
Rights: © Springer International Publishing Switzerland 2015.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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