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    Assessment of Association Rules based on Certainty Factor: an Application on Heart Data Set
    (Ieee, 2019) Akbas, Kubra Elif; Kivrak, Mehmet; Arslan, A. Kadir; Colak, Cemil
    Association rules mining is one of the uttermost applied techniques in data mining and artificial intelligence. Support and confidence are two basic measures employed in the evaluation of association rules. The rules obtained with these two values are often correct; however, they are not strong rules. Most of the rules, especially with a high support value, are misleading. For this reason, there are many interestingness measures proposed to achieve stronger rules. In this study it is aimed to establish strong association rules with variables in open sourced heart data set. In the current study, Apriori algorithm was used to obtain the rules. As a result of the analysis, only 55 confidence and support criteria were taken into consideration. For more powerful rules, certainty factor was used as one of the interestingness measure proposed in the literature, and it was concluded that only 26 of these rules were strong. As a result of the analysis of the findings obtained in the context of the research, it can be inferred that stronger rules can be obtained by using the certainty factor in association rules mining.
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    A Developed web-based software can easily fulfill the assumptions of correlation, classification and regression tasks in data processing
    (Ieee, 2019) Yasar, Seyma; Arslan, A. Kadir; Colak, Cemil; Yologlu, Saim
    There are many assumptions that should be provided in regression and correlation analyses. If the assumptions are not met, the results of the analysis lead to errors. Multivariate regression analyses are performed by many software. However, many of this software are commercial and platform dependent. In this study, open source web-based software is developed to test the assumptions of simple/multiple linear regression, simple/multiple logistic regression analysis and correlation analysis, which are classification and regression techniques in machine learning. This software also provides a statistical interpretation of the results to researchers.
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    Open Source Web Based Software for Random Assignment/Allocation Methods in Data Processing
    (Ieee, 2019) Arslan, A. Kadir; Balikci Cicek, Ipek; Colak, Cemil
    In this study, it is aimed to develop a user-friendly open-source web-based software which enables the assignment of the subjects included in the scientific research to the groups with equal probability. An open source R package, Shiny, is used to develop the recommended web tool. In the developed software, one of the required equilibrium methods; random allocation rule, truncated binomial design, maximal procedure design, complete randomization methods; complete randomization design, blocking methods; permuted block randomization with random block constellation, the Hadamard randomization, adaptive methods; the big stick design, Efron's biased coin design, Wei's urn design, generalized biased coin design, Chen's biased coin design are included. A random allocation rule, one of the random assignment methods, is applied to a hypothetical data set where the sample size is 140 and the number of groups are two. As a result, in the first group, a random assignment was made in such a way that the number of samples are 70 and the number of samples in the second group are 70. According to the hypothetical data set findings, the developed easily assigns the subjects to the study groups by using random assignment methods. Therefore, it is stated that it easily solved a significant bias problem in scientific studies. In the following stages of the study, the scope of the software can be expanded with the addition of techniques comparing the results of random assignment methods.
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    An Open Sourced Software for Data Transformation and an Application on Simulated Data
    (Ieee, 2019) Arslan, A. Kadir; Tunc, Zeynep; Colak, Cemil
    In this study, it is aimed to develop a new user-friendly web-based software to ensure the normal distribution of the new data set obtained by applying various mathematical transformations to data sets that do not meet the normal distribution from parametric hypothesis testing conditions. The web based software is developed by Shiny web framework, which is an open source R package. In the web-based software, arcsinh (x), Box-Cox, Exponential, Lambert W (h type), Lambert W (s type), Logarithmic, Square root, Yeo-Johnson data transformation methods are used. The software also allows us to decide on the best conversion for the data set to be transformed by calculating the Pearson P test statistic, which chooses on the best method in the methods used. This is done by selecting the conversion with the smallest Pearson P statistic. In order to evaluate the outputs of the software, a data set with three variables was derived with the Cauchy, gamma, Weibull distributions respectively and 500 samples were used for each distribution. The developed software is novel user-friendly web-based software that enables researchers to get more accurate results in their work and to obtain data transformation methods that provide parametric test assumptions known as more powerful tests.
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    Relationship between serum homocysteine levels and structural-functional carotid arterialabnormalities in inactive Behcet's disease
    (VIA MEDICA, UL SWIETOKRZYSKA 73, 80-180 GDANSK, POLAND, 2018) Yağmur, Jülide; Açıkgöz, Nusret; Cansel, Mehmet; Karıncaoğlu, Yelda; Ermiş, Necip; Pekdemir, Hasan; Arslan, A. Kadir
    Background: Behcet's disease (BD) is a chronic autoimmune disorder with symptoms manifesting from an underlying vasculitis. Since the disease activity is correlated with characteristic vascular endothelial dysfunction, BD places individuals at increased risk of cardiovascular diseases, such as atherosclerosis. Hyperhomocysteinaemia is an independent risk factor for arteriosclerotic vascular diseases. Aim: This study was designed to investigate how plasma homocysteine (Hcy) affects the structural and functional properties of the carotid artery in humans. Methods: Sixty-eight BD patients with subclinical atherosclerosis and 40 healthy controls underwent carotid sonography and Doppler ultrasound to measure carotid artery intima-media thickness (C-IMT) and carotid stiffness and distensibility (indicating elasticity). Total Hcy level was determined by enzyme-linked immunosorbent assay. For analysis, the BD patients were sub-grouped according to hyperhomocysteinaemia (>15 mu mol/L). Results: The patients with BD were found to have increased C-IMT and beta stiffness and decreased distensibility. In addition, hyperhomocysteinaemia was significantly correlated with these detrimental changes in the carotid artery, possibly raising the risk of these patients developing atherosclerosis. Conclusions: These findings suggest a potential mechanism of atherosclerosis in BD and highlight the processes that future research should focus on to address identification and prophylactic treatment of BD patients at risk of cardiovascular disease.