Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9544
Title: | Risk assessment for primary coronary heart disease event using dynamic bayesian networks |
Authors: | Orphanou, Kalia Stassopoulou, Athena Keravnou-Papailiou, Elpida |
metadata.dc.contributor.other: | Κεραυνού Παπαηλιού, Ελπίδα |
Major Field of Science: | Engineering and Technology |
Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering |
Keywords: | Dynamic Bayesian networks;Primary coronary heart disease;Risk assessment;Temporal abstraction;Temporal reasoning |
Issue Date: | 1-Jan-2015 |
Source: | 15th Conference on Artificial Intelligence in Medicine, 2015, Pavia, Italy |
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: | https://hdl.handle.net/20.500.14279/9544 |
ISBN: | 978-331919550-6 |
Rights: | © Springer International Publishing Switzerland 2015. |
Type: | Conference Papers |
Affiliation : | University of Cyprus University of Nicosia Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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