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|Title:||Risk assessment for primary coronary heart disease event using dynamic bayesian networks||Authors:||Orphanou, Kalia
|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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