• Neonatal Medicine
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• v.18 no.2
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• pp.221-227
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• 2011

Purpose: The objectives were to identify the characteristics of neonates with hydrops fetalis, and to identify the risk factors associated with mortality. Methods: A retrospective review of AMC (Asan Medical Center) dataset was performed from January 1990 to June 2009. The characteristics of 71 patients with hydrops fetalis were investigated and they were divided into two groups: the survived group and the expired group. Various perinatal and neonatal factors in two groups were compared to find out risk factors associated with mortality based on univariate analysis, followed by multiple regression analyses (SPSS version 18.0). Results: Of those 71 neonates (average gestational age: 33 weeks, birth weight: 2.6 kg), 38 survived, 33 died, resulting in overall mortality rate of 46.5%. The most common etiology was idiopathic followed by chylothorax, cardiac anomalies, twin-to-twin transfusion, meconium peritonitis, cardiac arrythmias, and congenital infections. Factors that were associated independently with mortality in logistic regression analyses were low 5-minutes Apgar score, hyaline membrane disease and delayed in achieving 50th percentile ideal body weight for appropriate gestational age by 10 days. Conclusion: In this study, 5-minutes Apgar score, hyaline membrane disease and delayed in achieving 50th percentile ideal body weight for appropriate gestational age by 10 days were significant risk factors associated with mortality in hydrops fetalis. Therefore, the risk of death among neonates with hydrops fetalis depends on the illness immediately after birth and severity of hydrops fetalis. Informations from this study may prove useful in prediction of prognosis to neonates with hydrops fetalis.

• Journal of Preventive Medicine and Public Health
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• v.31 no.3 s.62
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• pp.503-515
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• 1998

In order to investigate the factors influencing QOL and life satisfaction of the physically disabled, the author interviewed, by using structuralized questionnaire, 440 individuals among the physically disabled who were participated in Health Examination from April to July, 1997. The questionnaire consisted of the general characteristics(sex, age, marital status, family number, etc), the Reintegration to Normal Living Index(RNLI) to assess QOL, and the single item of five-likert scale to evaluate life satifaction. The means of RNLI were $16.2{\pm}4.8$ in total score, $12.2{\pm}3.4$ in daily functioning and $4.0{\pm}2.1$ in perception of self. The respondents were less reintegrated toward social activities and relationships than impairments or disabilities. While the satisfied group was 47.3%, the dissatisfied group was 52.7%. As the results of multiple regression and logistic regression analysis, the significant predictors of QOL were age, education, job, grade of disability and subjective health status. The life satisfaction were related to economic status, job and subjective health status. To improve QOL and life satisfaction of the physically disabled, it is important that we improve their basic socioeconomic status by getting a job through rehabilitation education and induce them to have positive self-assessment by extending the opportunity of social participation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.498-508
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• 2017

Purpose: The present study investigated nutrient supplement intake to examine the relationship between the health behaviors of nutrient supplement users and nonusers and nutrient supplement users and other drug users. The results provide baseline data to understand whether nutrient supplements actually perform as expected in view of the fact that healthy people that take nutritional supplements may become healthier, but may also develop nutritional supplement abuse problems. Among 7,006 household heads of 24,614 household members from the Korea Health Panel data in 2008, a total of 6,009 household heads were the respondents of the Korea Health Panel Survey (appendix) in 2009. Method: The subjects of the present study were targeted household heads. The respondents who reported that they had taken (planned to take) life/health promotion-related drugs (01. vitamins/nutritional supplements) for more than three months that were purchased at pharmacies during the past one year at the time of the survey were defined as nutritional supplement users. Those who took other drugs (05. hair-loss treatments, 06. obesity treatments, 10. others) were regarded as other drug users. A chi-squared test was performed to analyze the sociodemographic characteristics of the subjects and differences between groups. Multiple regression analyses were conducted to analyze health behaviors according to nutrient supplement intake. Result: Comparison of (A) nutritional supplement users and nonusers revealed that those who were women, 50 years or older, and spent more than average living expenses were more likely to take nutritional supplements, which was not significant in health behavior variables. Analysis of nutritional supplement users and other drug users (B) revealed that those who were high school graduates or above, had a spouse, were non-smokers, took drugs, ate regular meals, and were not stressed by economic or family conflicts were more likely to take nutritional supplements. Conclusion: The results of the present study indicated that people take nutritional supplements because of their psychological desire to be healthy, not because they are not healthy, have problems, or believe supplements will make them healthier.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of dental hygiene science
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• v.16 no.3
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• pp.242-248
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• 2016

The purposes of this study were to investigate the factors affection the Oral Impacts on Daily Performances for Children (C-OIDP) in elementary and middle school students, and identify the association between oral health-related behaviors, oral health condition and C-OIDP. A cross-sectional study was conducted in three schools in Incheon, Asan, Korea. A total of 175 selected children were interviewed by a trained examiner using a questionnaire. Oral Health Related Quality of Life was assessed by the Korean version of C-OIDP. Socio-economic characteristics, oral health-related behaviors, oral health condition and C-OIDP were verified using the questionnaire. ANOVA analysis was performed to determine the oral health and C-OIDP, and multiple regression analysis was performed to determine the factors affecting the C-OIDP. The activities with the greatest effect were eating (28.0%), cleaning teeth (22.9%), and smiling (18.9%). In the logistic regression model, the high item score of C-OIDP was associated with experiencing dental caries and gum pain in the past month. The more the C-OIDP prevalence item, the more the fillng deciduous tooth surface (fs) (p=0.024), caries experienced deciduous tooth surface (dfs) (p=0.049), total caries tooth surface (ds+DS) (p=0.021), and total caries experienced tooth surface (dfs+DMFS) (p=0.047). It can be concluded that the factors affecting C-OIDP are fs, dfs, dfs+DMFS, and gingival pain. Based on these results, we can improve C-OIDP to advance preventive practice.

• Journal of Preventive Medicine and Public Health
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• v.29 no.2 s.53
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• pp.199-214
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• 1996

To investigate the factors which affecting the cognitive function and depression of the 65 or more age group, the authors surveyed for the subjects in the region of Taejon and nearby Taejon area. 729 studied subjects were tested for cognitive function with MMSE and depression with GDS. The main results were followings; In the studied subjects, the rate of normal cognitive function was 56.8%, the rate of mildly impaired was 24.1% and the rate of severe impairment was 19.1%. The cognitive function level was closely related to the depression score. As the age increased, the cognitive function was more impaired. Sexual difference was also existed in the cognitive function level and the depression score. After adjusting the effect of age, the variables such as sex, marital status, education level, past job, instrumental ability of daily living, regular physical exercise, frequencies of going out the house, chest discomfort, visual and auditory disturbance, and dizziness had the significant relationship with cognitive function impairment. Among these variables instrumental ADL, age, visual disturbance, and sex showed statistical significance in the logistic regression model. In the multiple stepwise regression, the variables which had significant relationship to depression score were education level, frequencies of going out house, current job and house work activity, regular physical exercise, instrumental ADL, self-rated health and nutritional status, dimness, visual disturbance, and chest pain. In conclusion, main characteristics which had close relationship to the cognitive function and depression symptoms in the studied subjects were physical function and self rated health status.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.3 no.1
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• pp.17-22
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• 2000

Purpose: This study was conducted to evaluate the association between H. pylori infection and socioeconomic status and to determine the current prevalence of H. pylori infection in Korean adolescents. Methods: A structured questionnaire was sent to the children's parents to obtain demographic information on the parents and environmental information. Of the 532 questionnaires sent out, 375 (70.5%; 170 girls and 205 boys) were returned. Their ages ranged from 10 to 15 years (mean, 12.9 years). After collecting blood samples, we measured serum IgG antibody to H. pylori using ELISA method. The association of risk factors such as age, sex, socioeconomic class, type of house, and crowding index with H. pylori infection were analyzed by multiple regression analysis. Socioeconomic status was estimated from the parents' education and occupation using a modified Hollingshead index. Results: The prevalence rate of H. pylori infection was 16.8% (63/375). It increased with age (10.3% at 10~11 years, 15.9% at 12~13 years, and 20.7% at 14~15 years). The H. pylori infection was inversely related to the socioeconomic class (6.3% for the upper class, 16.0% for the middle class, and 20.0% for the lower calss). Crowding condition and type of house did not affect significantly on seroprevalence of H. pylori infection. After logistic regression, we found that the odds ratio for age was 2.2 (95% confidence interval 0.9~5.4), and for socioeconomic status, 3.6 (95% confidence interval 0.5~28.9). Conclusion: The prevalence of H. pylori infection in Korean adolescents was 16.8%. It related inversely to socioeconomic status but was not statistically significant. Socioeconomic status based on parents' education and occupation seemed to affect more on H. pylori seroprevalence than crowding or type of house did.

• Journal of Preventive Medicine and Public Health
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• v.42 no.2
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• pp.89-95
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• 2009

Objectives : To assess the protective effects of wearing protective devices among the residents and volunteers who participated in the cleanup of the Hebei Spirit oil spill. Methods : A total of 288 residents and 724 volunteers were surveyed about symptoms, whether they were wearing protective devices and potential confounding variables. The questionnaires were administered from the second to the sixth week following the accident. Spot urine samples were collected and analyzed for metabolites of 4 volatile organic compounds(VOCs), 2 polycyclic aromatic hydrocarbons(PAHs), and 6 heavy metals. The association between the wearing of protective devices and various symptoms was assessed using a multiple logistic regression adjusted for confounding variables. A multiple generalized linear regression model adjusted for the covariates was used to test for a difference in least-square mean concentration of urinary biomarkers between residents who wore protective devices and those who did not. Results : Thirty nine to 98% of the residents and 62-98% of volunteers wore protective devices. Levels of fatigue and fever were higher among residents not wearing masks than among those who did wear masks(odds ratio 4.5; 95% confidence interval 1.23-19.86). Urinary mercury levels were found to be significantly higher among residents not wearing work clothes or boots(p<0.05). Conclusions : Because the survey was not performed during the initial high-exposure period, no significant difference was found in metabolite levels between people who wore protective devices and those who did not, except for mercury, whose biological half-life is more than 6 weeks.

• Korean Journal of Psychosomatic Medicine
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• v.15 no.1
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• pp.35-43
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• 2007

Objectives : Recently, many authors investigated the relation of temperament and character to seasonality and the genetic factors in seasonality and personality. In this study, we investigated the relation between personality structure obtained from the psychobiological Temperament and Character Inventory (TCI) and self-reported seasonal variations in mood and behavior measured by the Seasonal Pattern Assessment Questionnaire (SPAQ). Methods : 600 high-school students who live in Seoul of Korea, were participated in this study. Subjects were surveyed with the Korean translation of the SPAQ of Rosenthal, an instrument for investigating mood and behavioral changes with respect to the seasons of the you. Korean version of the TCI of Cloninger was also used for assessment of personality. Results : Female students were significantly higher scores on harm avoidance, reward dependence, and cooperativeness than male students who had significant higher scores on persistence and self·transcendence than the formers. GSS were showed positive correlation with harm avoidance and self-transcendence, and negative correlation with cooperativeness and self-directedness. By employing logistic regressions, the regression coefficients of SAD were significantly negative in SD, and positive in ST. Also, the regression coefficients of S-SAD were significantly negative in CO, and positive in ST. Those with GSS at least 11 were significantly higher mean ST values compared to the remaining individuals, and those with worst in winter were significantly lower mean CO values compared to the remaining individuals. Those who considered the seasonality as a problem at least to a moderate degree were associated with high HA and ST. Conclusion : We add the evidence that the seasonality is related to the temperament and character. Although there have been many reports about the seasonality in relation to the temperament and character in foreign countries, there has been very limited report from Korea before. We hope that this result would be a helpful in the clinical field in Korea.