[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 4, Issue 2 (9-2017) ::
2017, 4(2): 108-121 Back to browse issues page
Detection of Crimean-Congo Fever Using C4.5 Decision Tree
Reza Esmaeeli Gohari , Elham Esmaeeli Gohari , Mehdi Shafiei
. M. Sc. in Compter Engineering, Computer Engineering Det., Technical and Engineering Campus, Yazd University, Yazd, Iran
Abstract:   (1365 Views)
Introduction: The prevalence of Crimean-Congo fever, a common disease between human and animal, shows an increasing rate by coming summer season. Detection of this disease by the use of necessary tests, lasts at least about one week. There are several data mining and machine learning techniques to create predictive models for identifying at risk people. In this study, C4.5 decision tree method has been used due to its simplicity and efficiency.
Methods: In this applied descriptive study, data related to suspected cases of Crimean-Congo fever were used. These data have been collected from health centers of Iran in a four-year period since 2014 and contained 965 records with 29 features. First, by using the quadratic programming feature selection method, the variables which were effective on the model were selected and then, the C4.5 decision tree model was created through using input variables and determining the target variable. Data analysis was performed through Matlab software.
Results: According to the applied model, it was found that fever, bleeding, sudden onset of symptoms, increased liver enzyms, increased total Bilirubin, decreased Hemoglobin, Hematuria, Leukocytosis, Proteinuria and Leukopenia have the greatest impact in the diagnosis of this disease.
Conclusion: According to the obtained results, the sensitivity of the proposed model is 95% and its specificity is 50%. Therefore, this model showed acceptable efficiency in diagnosing this disease in comparison with other studies done in medical data mining field.
 
Keywords: Medical decision support system, Disease diagnosis, Crimean-Congo hemorrhagic fever, C4.5 Decision tree
Full-Text [PDF 1128 kb]   (583 Downloads)    
Type of Study: Original Article | Subject: Data Mining
Received: 2017/07/23 | Accepted: 2017/09/18
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA code


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Esmaeeli Gohari R, Esmaeeli Gohari E, Shafiei M. Detection of Crimean-Congo Fever Using C4.5 Decision Tree. Journal of Health and Biomedical Informatics. 2017; 4 (2) :108-121
URL: http://jhbmi.ir/article-1-225-en.html


Volume 4, Issue 2 (9-2017) Back to browse issues page
مجله انفورماتیک سلامت و زیست پزشکی Journal of Health and Biomedical Informatics
Persian site map - English site map - Created in 0.06 seconds with 30 queries by YEKTAWEB 3781