• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Journal of Elementary Mathematics Education in Korea
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• v.22 no.2
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• pp.143-159
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• 2018

Since the mathematics learning achievement level is closely related to problem-solving ability, it is necessary to understand the relationship between problem-solving ability and meta-affect ability from the point of view of general mathematics learning ability. In this study, we compared the frequency analysis and the case analysis of the functional aspects of the meta-affect in elementary school students' problem-solving processes according to mathematics learning achievement level in parallel with frequency analysis and case analysis. In other words, the frequency of occurrence of meta-affect, the frequency of meta-affective type, and the frequency of meta-functional types of meta-affect were compared and analyzed according to the mathematics learning achievement level in the collaborative problem-solving activities of small group members with similar mathematics learning achievement level. In addition, we analyzed the representative cases of meta-affect by meta-functional types according to the mathematics learning achievement level in detail. As a result, meta-affect in problem-solving processes of the upper level group acted as relatively various types of meta-functions compared to the lower level group. And, the lower level group, the more affective factors acted in the problem-solving processes.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.4
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• pp.1133-1142
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• 2016

The purpose of this study was to verify the effects of science classes using abductive strategies on the scientific concept understanding and meta-cognition. The subjects included two classes of sixth graders from K Elementary School in B Metropolitan City and they divided into two groups. Research group was composed of 21 students(10 boys, 11 girls) and comparative group was composed of 21 students(11 boys, 10 girls). In order to achieve aims of this study, proper contents to apply abductive strategies were selected from the first semester science curriculum for sixth graders. Also five-steps study papers were designed to elicit abductive reasoning. While the research group received 20 times of reframed science lessons using abductive strategies, the comparative group received common science lessons according to the teachers' manual. The results of this study are as follows. First, science classes using abductive strategies were effective for the scientific concept understanding. Also there were statistically significant differences between the research group and the comparative group in overall science sub-domain. In the process of hypothesis formulating, students tried to find out scientific causes thoroughly to present the optimal explanation and they concentrated on the analysis of each scientific concept. It is thought that this process contributed to better understanding in scientific concepts. Second, science classes using abductive strategies were effective for improving meta-cognition. There were statistically significant differences between the two groups and especially in monitoring that is one of sub-factors of meta-cognition. It indicates that hypothesis formulating process gave positive effect on meta-cognition by stimulating critical thinking and manifesting elaboration.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.5
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• pp.425-437
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• 2001

This study is based on the uses meta-analysis methodology to examine the statistical consistency and importance of random variation among results of epidemiologic studies between air pollutants exposure and childhood asthma. Studies for this meta-analysis were conducted by reviewing previous results and by asking researcher active in this field for recommendations. Overall, 10 cases of air pollutants exposures and childhood asthma were reviewed. A variety of statistical methods for meta-analysis have been used to assess the combined effects, to identify heterogeneity, and to provide a single summary risk estimate based on a set of simiar epidemiologic studies. In this study, classification of exposure metircs on air environmental epidemiologic studies are reported for (1) aggravation of childhood asthma by a 50 ppb increase SO$_2$(6 individual studies); (2) aggravation of childhood asthma by a 50 ppb increase NO$_2$(5 individual studies); (3) aggravation of childhood asthma by a 50 ppb increase $O_3$(7 individual studies); (4) aggravation of childhood asthma by a 10$\mu\textrm{g}$/m$^3$increase PM$_{10}$ (4 individual studies); (5) aggravation of childhood asthma by a 1 ppm increase CO (2 individual studies); and (6) comparison of results between a Korean study results and this meta-analytic study. Results of this study indicated that an inverse-variance weighted pooling of the hospital admission risk at a 1ppm increment of CO levels was 1.12% (95% CI : 1.01 ~ 1.24). The hospital admission risk was estimated to increase 5% (95% CI : 1.02~1.08), 6%(95% CI : 1.04~1.09), and 5% (95% CI : 1.02~1.09) with each 50ppb increase of SO$_2$, NO$_2$, and $O_3$, respectively. In addition, our results lead to a small but significant elevation in risk of 2% (RR = 1.02, 95% CI = 1.01~1.04) with each 10$\mu\textrm{g}$/m$^3$increase of PM$_{10}$ among 4 individual studies. We found a small elevation in risk of childhood asthma, and pooled results of 10 epidemiologic studies of childhood asthma using increase a cut-off-point levels of air pollutants showed a few pieces of evidence. The results of this meta-analysis suggested that air pollution associated with an increased incidence of childhood asthma. According to this study, relationship between exposure to air pollutants and childhood asthma in Korea seem to be high than results of this meta-analysis.sis.

• Research in Mathematical Education
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• v.24 no.3
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• pp.175-199
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• 2021

The Science Writing Heuristic (SWH) approach is described as an immersive argument-based science inquiry focusing particularly on learning through epistemic practices. In the literature, several previous studies indicate how academic achievement is positively influenced by the SWH. In addition to these previous studies, several meta-syntheses of qualitative data have been conducted on this particular topic. With these literatures in mind, a quantitative meta-analysis was conducted with ten studies (N = 724) to examine the effectiveness of the SWH on student achievement in Turkey. To present a thoroughly detailed report, this study also examined the following moderators: grade level, subject area, school location, intervention length, and report source. Overall, this study found that in Turkey, the SWH classrooms performed better in academic achievement tests than traditional lecture-based classrooms. Additionally, the SWH is more likely to be effective regardless of grade levels, subject areas, and school locations.

• The Korean Journal of Pain
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• v.30 no.4
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• pp.250-257
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• 2017

Vitamin D is a cofactor responsible for autoimmune disorders. There is no agreement in the studies investigating the association between vitamin D and fibromyalgia. This study aims to combine the conflicting results of the primary studies which compared these patients with control groups regarding the serum concentration of vitamin D. This meta-analysis has been designed based on PRISMA guidelines. Relevant keywords were searched in PubMed, Science direct, Scopus, Cochrane, and Google scholar and primary studies were selected. After screening the eligible studies according to inclusion/exclusion criteria, we investigated the risk of bias in the selected studies and also the heterogeneity between the primary results using Cochrane (Q) and I-squared ($I^2$) indices. The primary results were combined using inverse variance method and Cohen statistics as well as a random effects model. Publication bias was assessed using Egger test. Sensitivity analysis was applied to investigate the influence of each primary study on the final result of the meta-analysis. Suspected factors in the heterogeneity were assessed using meta-regression models. We entered 12 eligible studies in the meta-analysis including 851 cases compared with 862 controls. The standardized mean difference of Vitamin D between the two groups was -0.56 (95% confidence interval: -1.05, -0.08). Our meta-analysis showed that vitamin D serum levels of patients with fibromyalgia was significantly lower than that of control group.

• Research in Community and Public Health Nursing
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• v.29 no.1
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• pp.120-132
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• 2018

Purpose: This study is a systematic review and meta-analysis designed to investigate effects of alcohol management programs for Korean university students. Methods: Research results published until October 14, 2016 were systematically collected in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis). A total of 12 papers were selected for the meta-analysis. To estimate the effect size, meta-analysis of the studies was performed with the Comprehensive Meta-Analysis 3.0. Results: The mean effect size of 12 studies in total (Hedges' g=-0.36; 95% Confidence Interval [CI]: -0.76~0.05) was not significant statistically. In a study of college students classified as problematic drinking (total of 9), the drinking program showed a median effect size of Hedges' g=-0.57(95% CI: -0.96~-0.18). Results of the drinking-related outcome variables showed a significant effect size (Hedges' g=-0.61; 95% CI: -1.10~-0.13), but psychosocial related outcome variables were not significant (Hedges' g=-0.50; 95% CI: -1.24~0.23). Conclusion: It can be seen that the alcohol management program for college students has a significant effect on controlling the problem drinking of college students. In addition, application of a differentiated drinking program with problem drinkers selected as a risk group will be effective in controlling drinking and drinking related factors.

• Communications of Mathematical Education
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• v.35 no.4
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• pp.359-376
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• 2021

In this study, in accordance with the research trend that the learner's emotions expressed positively or negatively in mathematics learning or the learner's beliefs and attitudes toward mathematics learning affect the results of mathematics learning, the learner's emotions and affective factors are analyzed in the learner's own learning. A power that can be adjusted according to a goal or purpose is needed, and I tried to explain this power through meta-affect. To this end, the meaning of the definitional and conceptual factors of meta-affect was explored based on prior studies. Affective factors of meta-affect were viewed as emotions, attitudes, and beliefs, and conceptual factors of meta-affect were viewed as awareness, evaluating, controlling, utilization, and monitoring, and the meaning of each conceptual factor was also defined. In this study, the conceptual factors and meanings of meta-affect in terms of using them to help in learning mathematics by controlling them, beyond the identification or examination of the characteristics of the affective factors, which are meaningfully dealt with in the field of mathematics education.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.7 no.2
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• pp.93-98
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• 2021

meta-iodobenzylguanidine is one of the norepinephrine analogs and reuptakes together with norepinephrine with norepinephrine transporter. The radioiodinated ligand, ¹²³I-meta-iodobenzylguanidine, is the most widely used for single photon emission computed tomography imaging to diagnose functional abnormalities and tumors of the sympathetic nervous system. In this study, we performed cellular uptake studies of ¹²³I-meta-iodobenzylguanidine in positive- and negative-norepinephrine transporter cells in vitro to verify the uptake activity for norepinephrine transporter. After ¹²³I-meta-iodobenzylguanidine was injected via a tail vein into normal mice, Single photon emission computed tomography/computed tomography images were acquired at 1 h, 4 h, and 24 h post-injection, and quantified the distribution in each organ including the adrenal medulla as a norepinephrine transporter expressing organ. In vitro cell study showed that ¹²³I-meta-iodobenzylguanidine specifically uptaked via norepinephrine transporter, and significant uptake of ¹²³I-meta-iodobenzylguanidine in the adrenal medulla in vivo single photon emission computed tomography images. These results demonstrated that single photon emission computed tomography imaging with ¹²³I-meta-iodobenzylguanidine were able to quantify the biodistribution in vivo in the adrenal medulla in normal mice.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.355-369
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• 2022

Objective: To evaluate the completeness of the reporting of systematic reviews and meta-analyses published in a general radiology journal using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Materials and Methods: Twenty-four articles (systematic review and meta-analysis, n = 18; systematic review only, n = 6) published between August 2009 and September 2021 in the Korean Journal of Radiology were analyzed. Completeness of the reporting of main texts and abstracts were evaluated using the PRISMA 2020 statement. For each item in the statement, the proportion of studies that met the guidelines' recommendation was calculated and items that were satisfied by fewer than 80% of the studies were identified. The review process was conducted by two independent reviewers. Results: Of the 42 items (including sub-items) in the PRISMA 2020 statement for main text, 24 were satisfied by fewer than 80% of the included articles. The 24 items were grouped into eight domains: 1) assessment of the eligibility of potential articles, 2) assessment of the risk of bias, 3) synthesis of results, 4) additional analysis of study heterogeneity, 5) assessment of non-reporting bias, 6) assessment of the certainty of evidence, 7) provision of limitations of the study, and 8) additional information, such as protocol registration. Of the 12 items in the abstract checklists, eight were incorporated in fewer than 80% of the included publications. Conclusion: Several items included in the PRISMA 2020 checklist were overlooked in systematic review and meta-analysis articles published in the Korean Journal of Radiology. Based on these results, we suggest a double-check list for improving the quality of systematic reviews and meta-analyses. Authors and reviewers should familiarize themselves with the PRISMA 2020 statement and check whether the recommended items are fully satisfied prior to publication.