DocumentCode :
3777093
Title :
Ebola virus disease detection using Dempster-Shafer evidence theory
Author :
Andino Maseleno; Fauzi;Muhammad Muslihudin
Author_Institution :
STMIK Pringsewu, Lampung, Indonesia
fYear :
2015
Firstpage :
579
Lastpage :
582
Abstract :
This research presents Ebola virus disease detection using Dempster-Shafer evidence theory. The Dempster-shafer evidential theory is a method about uncertainty reasoning, and this theory reduces the requirements of the knowledge of prior probability and conditional probability. Between 1976 and 2013, the World Health Organization report a total of 24 outbreaks involving 1,716 cases. The existing methods used detect Ebola virus disease are complex, time consuming, can only be performed under laboratory conditions, often require highly trained lab workers and time-intensive procedures, as well as a highly sterile experimental environment. The main contribution of this research is to consider Dempster-Shafer evidence theory for Ebola virus disease detection by combined each symptom. The result reveals that Ebola virus disease detection using Dempster-Shafer evidence theory obtained degree of belief 0.85.
Keywords :
"Diseases","Uncertainty","Cognition","Hafnium","Hemorrhaging","Measurement uncertainty","Mathematical model"
Publisher :
ieee
Conference_Titel :
Progress in Informatics and Computing (PIC), 2015 IEEE International Conference on
Print_ISBN :
978-1-4673-8086-7
Type :
conf
DOI :
10.1109/PIC.2015.7489914
Filename :
7489914
Link To Document :
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