Dengue fever prediction modelling using data mining techniques

Buathong, Wipawan; Jarupunphol, Pita

doi:10.1504/ijdmb.2021.116891

Cited by 3 publications

(3 citation statements)

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“…Once the qualities are more linked with 'X' than with the tested class, the main correlation feature then becomes apparent. A "symmetric uncertainty" (SU) rating coefficient, which is utilized to gauge the degree of feature "conditional uncertainty," and the X divided by Y criteria are used to construct the FCBF's characterization and redundancy analysis concept [30].…”

Section: Chi-square ( χ 2 )mentioning

confidence: 99%

Yapay Sinir Ağları Kullanılarak Pediatrik Akciğer Röntgen Görüntülerinden Pnömoni Tespiti

DÜNDAR,

KOÇER

2023

Journal of Polytechnic

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Pneumonia Detection from Pediatric Lung X-Ray Images Using Artificial Neural Networks ABSTRACT Studies on medical imaging have grown significantly in recent years. Doctors have a crucial convenience for diagnosis thanks to semi- or fully automatic region recognition in medical imaging. It is crucial to support treatment without a specialist doctor, particularly in those nations where there is a dearth of such medical professionals. The little air sacs known as alveoli are most impacted by pneumonia, a lung inflammation. A key component of providing the right therapy conditions to heal patients and reduce harm while eradicating inflammation is early detection and precise diagnosis. Noise and blurring in patient photos obtained from X-ray machines are cleaned using deep learning algorithms and image processing techniques, and they are very helpful in. In this study, we studied chest X-ray images of pediatric patients with pneumonia and healthy individuals. XGBoost (eXtreme gradient boosting) is an innovative machine learning algorithm based on decision tree and using gradient boosting in its computations. It achieved 97.01% success with high classification performance. Keywords: Medical imaging, Machine learning, Pediatric Chest X-ray

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Section: Chi-square ( χ 2 )mentioning

confidence: 99%

Yapay Sinir Ağları Kullanılarak Pediatrik Akciğer Röntgen Görüntülerinden Pnömoni Tespiti

DÜNDAR,

KOÇER

2023

Journal of Polytechnic

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“…Data mining is recognized as an efficient technique for identifying and selecting a data sample or "data dimension" from a considerable amount of data (Bhatia, 2019). It is one of the most outstanding data analysis methods as it acquires new knowledge from big data (Buathong & Jarupunphol, 2021). There are several data mining applications categorized into specific perspectives.…”

Section: Data Mining Applicationsmentioning

confidence: 99%

ARM for Analyzing Factors Influencing Vaccinations During the COVID-19 Outbreak

Buathong

Jarupunphol

2023

JDSIS

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This article investigates factors influencing Coronavirus 2019 (COVID-19) vaccinations and public concerns using association rule mining (ARM). The experiment was conducted in Phuket at the beginning of 2022 when many people were still not vaccinated. The online questionnaire comprises 26 questions with a sample of 403 participants living in Phuket, Thailand. Among the participants, 377 people were vaccinated. The experiment is based on two main ARM methods: Apriori and FP-Growth. The performance assessment criteria were 0.5 and 0.6 minimum support and 0.9 and 1.0 minimum confidence. The most appropriate values are based on 0.5 minimum support and 1.0 minimum confidence with lift > 1. The experimental results reveal factors influencing COVID-19 vaccinations in association rules. For example, most vaccinated people received Sinovac. They are female and knowledgeable about vaccines. They are concerned about severe illness or death and live in the Mueang district more than others. They are also concerned about injection site pain, nausea, vomiting, numbness, and hemiplegia. Enhancing herd immunity is another compelling reason for people to be vaccinated. In the meantime, these derived rules can be reversed to explain why many people are not vaccinated. For instance, the most available vaccine is Sinovac, and several vaccination points are in the Mueang district.

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“…ese problems lead to a great reduction in the speed and accuracy of data mining. erefore, using pure static data capture technology to establish data mining model is always not conducive to the development of data mining technology [4]. Due to the increasingly large data set and the increasing number of internal dynamic nodes faced by data mining, the controllability and predictability of each node are not high, and it is difficult to judge and determine the wrong data mining node.…”

Section: Introductionmentioning

confidence: 99%

Research on Data Mining of Sports Wearable Intelligent Devices Based on Big Data Analysis

Zong

Zhang

2022

Discrete Dynamics in Nature and Society

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Traditional motion data mining models have some problems, such as poor dynamic data capture effect, low information classification effect rate, poor quantitative representation effect, and so on. Based on this, this paper studies the mining method of dynamic motion data based on neural network, constructs a data mining model based on discrete dynamic modeling technology, and realizes the collection of data information from the aspects of motion characteristics and types combined with multilayer sensors. Neural network algorithm is used for comprehensive analysis to realize multivariate analysis and objective evaluation of all data of dynamic motion process and accurate analysis and evaluation according to different data characteristics of different types of motion data. The results show that the data mining model based on discrete dynamic modeling technology and wearable sensor technology has the advantages of high feasibility, high intelligence, and wide application range.

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Dengue fever prediction modelling using data mining techniques

Cited by 3 publications

References 0 publications

Yapay Sinir Ağları Kullanılarak Pediatrik Akciğer Röntgen Görüntülerinden Pnömoni Tespiti

Yapay Sinir Ağları Kullanılarak Pediatrik Akciğer Röntgen Görüntülerinden Pnömoni Tespiti

ARM for Analyzing Factors Influencing Vaccinations During the COVID-19 Outbreak

Research on Data Mining of Sports Wearable Intelligent Devices Based on Big Data Analysis

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