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DOI: 10.14569/IJACSA.2016.070761
PDF

An Emergency Unit Support System to Diagnose Chronic Heart Failure Embedded with SWRL and Bayesian Network

Author 1: Baydaa Al-Hamadani

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 7, 2016.

  • Abstract and Keywords
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Abstract: In all the regions of the world, heart failure is common and on raise caused by several aetiologies. Although the development of the treatment is fast, there are still lots of cases that lose their lives in emergence sections because of slow response to treat these cases. In this paper we propose an expert system that can help the practitioners in the emergency rooms to fast diagnose the disease and advise them with the appropriate operations that should be taken to save the patient’s life. Based on the mostly binary information given to the system, Bayesian Network model was selected to support the process of reasoning under uncertain or missing information. The domain concepts and the relations between them were building by using ontology supported by the Semantic Web Rule Language to code the rules. The system was tested on 105 patients and several classification functions were tested and showed remarkable results in the accuracy and sensitivity of the system.

Keywords: Ontology Engineering; Bayesian Network; Heart Failure; Expert System; Validation Test

Baydaa Al-Hamadani, “An Emergency Unit Support System to Diagnose Chronic Heart Failure Embedded with SWRL and Bayesian Network” International Journal of Advanced Computer Science and Applications(IJACSA), 7(7), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070761

@article{Al-Hamadani2016,
title = {An Emergency Unit Support System to Diagnose Chronic Heart Failure Embedded with SWRL and Bayesian Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070761},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070761},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {7},
author = {Baydaa Al-Hamadani}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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