2023
DOI: 10.1016/j.matpr.2021.07.270
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Ensemble machine learning based prediction of dengue disease with performance and accuracy elevation patterns

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Cited by 32 publications
(15 citation statements)
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“…The second issue is that their illnesses are frequently difficult to distinguish from one another. They all have similar symptoms, which include arthralgia, fever, headache, myalgia, and orbital pain [ 4 ], among other things. Although the symptoms of Dengue, Zika, and Chikungunya are distinct from one another [ 5 , 6 ], all of them, except for Chikungunya, which is associated with joint discomfort, necessitate a high level of clinical competence and understanding in order to be accurately diagnosed.…”
Section: Introductionmentioning
confidence: 99%
“…The second issue is that their illnesses are frequently difficult to distinguish from one another. They all have similar symptoms, which include arthralgia, fever, headache, myalgia, and orbital pain [ 4 ], among other things. Although the symptoms of Dengue, Zika, and Chikungunya are distinct from one another [ 5 , 6 ], all of them, except for Chikungunya, which is associated with joint discomfort, necessitate a high level of clinical competence and understanding in order to be accurately diagnosed.…”
Section: Introductionmentioning
confidence: 99%
“…There are five classification methods implemented in this study, consisting of C.45, DT, KNN, RF, and SVM. Those classification method has been successfully implemented in several previous studies [6], [8], [16]. Classification is done using a cross-validation technique with k-fold 3, 5, and 10 to distribute training and testing data [6].…”
Section: Classificationmentioning
confidence: 99%
“…According to the World Health Organization (WHO), this disease is estimated to have a global burden of 50 million illnesses annually, and about 2.5 billion people worldwide live in dengue-endemic areas [18]. A person can develop dengue fever with various symptoms, such as headache, muscle aches, fever, and a measles-like rash, also known as fracture fever [16]. Regarding statistical data in varied countries, several dengue-endemic cases were reported in Saudi Arabia, especially in the western and southern provinces of the Jeddah and Mecca areas, the first in 2011, when 2,569 cases were reported, and the second, in 2013 when 4,411 cases including 8 deaths were reported.…”
Section: Introductionmentioning
confidence: 99%
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“…Performance analysis is carried out on LR, DT, RF, NB, KNN, SVM, AB, and XGBoost. In [ 28 ], the authors utilize an ensemble ML technique in hybrid integrations to predict dengue disease getting high accuracy. In [ 29 ], ML approaches such as Bayesian regression neural network, cubist regression, KNN, quantile random forest, and support vector regression are used stand-alone and coupled with variational mode decomposition for predicting COVID-19 cases.…”
Section: Introductionmentioning
confidence: 99%