• Korean journal of applied entomology
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• v.54 no.2
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• pp.73-81
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• 2015

A Cohort based model for temperature-dependent population dynacmics of Riptortus pedestris was constructed by using a commercial software (DYMEX) and seasonal occurrence along with pesticide treatments effect was simulated and validated with pheromone trap data. Ten modules of DYMEX software were used to construct the model and Lifecycle module was consisted of seven developmental stages (egg, 1 - 5 nymphal instars, and adult) of R. pedestirs. Simulated peaks of adult populations occurred three or four times after the peak of overwintered populations which was similar to those observed from pheromone trap catch. Estimated dates for the second peak were quite similar (1-2 day difference) with those observed with pheromone trap. However, the estimated dates for the first population peak were 9-16 days later than the observed dates by pheromone trap and the estimated dates for the last peak were 17-23 days earlier than the observed dates. When insecticide treatments were included in the simulation, the biggest decrease in R. pedestris adult density occurred when insecticide was applied on July 1 for the first peak population: the estimated adult density of the second peak was 3% of untreated population density. When insecticide was assumed to be applied on August 30 for the second peak population, the estimated adult density of the following generation was about 25% of untreated population and the peak density of the following generation reached about two weeks later than untreated population. These results can be used for the efficient management strategies for the populations of R. pedestris.

• Research in Plant Disease
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• v.12 no.3
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• pp.213-220
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• 2006

In year 2003, a soybean(Glycine max) sample showing severe dwarfing symptom was collected from a farmers' field in Cheongsong in Korea. The results from the diagnosis of the sample by RT-PCR revealed that it was infected by Soybean dwarf virus(SbDV), SbDV-L81. This study could be the first report of the occurrence of the virus in Korea. To further characterize the virus, the partial nucleotide sequence of the genomic RNA of SbDV-L81 was determined by RT-PCR using species-specific primers. The sequences were analyzed and subsequently compared to previously characterized strains of SbDV based on the pattern of symptom expression and vector specificities. The intergenic region between ORF 2 and 3 and the coding regions of ORF 2, 3 and 4 were relatively similar to those of dwarfing strains(SbDV-DS and DP) rather than those of yellowing strains(SbDV-YS and YP). Likewise, the result from the analysis of 5'-half of the coding region of ORF5 indicated that SbDV-L81 was closely related to strains(SbDV-YP and DP) transmitted by Acyrthosiphon pisum. These data from the natural symptom and the comparisons of five regions of nucleotide sequences of SbDV suggested that SbDV-L81 might be closely related SbDV-DP.

• Childhood Kidney Diseases
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• v.4 no.2
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• pp.92-101
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• 2000

Purpose : We analyzed the demogaphic data md clinical course of Korean children with chronic renal failure (CRF) observed between 1990 and 1999. Patients and Methods : Questionnaires were mailed to all children's hospitals ail through the country. We asked for primary renal disease age and serum creatinine levels at first presentation with CRF and end-stage renal disease (ESRD), and modes of renal replacement therapy (RRT). Results : 401 children (254 boys, 147 girls) with CRF, defined as a permanent increase of serum creatinine above 1.2 mg/dl for at least 3 months or until death, were identified. This represents an incidence of 3.68 per million child population per year. Of these patients, 22$\%$ on younger than 5 years, 28$\%$ 5 to 10 years and 50$\%$ 10 to 15 year. Eight five $\%$ of the patients could be classified with a primary renal disease. The most frequent cause is glomerulonephritis (36$\%$), followed by chronic pyelonephritis (21$\%$), renal hrpo/dylplasia (9$\%$), and hereditary nephropathies (7$\%$). Reflux nephropathy (16$\%$) was the most common single cause of CRF. ESRD was reached in 70$\%$ of all patient. 99.3$\%$ of these started RRT. Hemodialysis (HD, 42$\%$), peritoneal dialysis (PD, 35$\%$) and transplantation (TP, 23$\%$) were performed as the initial mode of RRT. A total of 161 TPs were performed (159 first grafts, 2 second grafts). A total of 32 patients died. The main causes of death were dialysis related complication in HD patients and infections in PD patients. Survival rate on any form of RRT was 88.7$\%$ during the mean follow-up period of 37 months. Conclusion Major efforts should be directed toward earlier diagnosis and treatment of reflux nephropathy to prevent occurrence of Of. Dialysis and TP have now become well accepted forms of treatment in Korean children with ESRD.

• Horticultural Science & Technology
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• v.32 no.5
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• pp.673-683
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• 2014

This study was conducted to establish an efficient screening method to identify cucurbits resistant to powdery mildew. Powdery mildew fungus was obtained from a single lesion of infected cucumber leaf in 2010 at Daejeon. The fungus was identified as Podosphaera xanthii race 1 based on morphological characteristics and resistance responses of four melon differentials. Development of powdery mildew caused by the fungal isolate on 34 commercial cultivars of cucumber was investigated at three plant growth stages in a greenhouse. The degree of resistance of cotyledons of each cultivar to the fungus was not correlated with that of whole plant, but powdery mildew occurrence in the first true leaf was highly correlated with resistance at the level of the whole plant. Based on these results, the first true leaf of cucurbit cultivars can be used for screening of resistance to powdery mildew. In addition, variation of resistance of commercial 12 cucumber and 26 melon cultivars to the powdery mildew fungus due to different growing seasons was tested. In the case of cucumber, the resistance response in some cultivars was influenced by growing season. The resistant cultivars showed higher resistance in the warm season than in the cool season. By contrast, the resistant melon cultivars demonstrated strong resistance in all the tested growing seasons. Interestingly, the tested powdery mildew pathogen, a member of P. xanthii race 1, was not pathogenic on seven cultivars of watermelon (Citrullus lanatus). To follow up on this, diverse race 1 isolates of P. xanthii should be collected and tested.

• The Korean Journal of Mycology
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• v.34 no.1
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• pp.39-53
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• 2006

This studies investigated the effect of concentrations of sodium chloride (NaCl) on occurrence and growth of fruitbody in oyster mushrooms, Pleurotus spp. Our experiments divided into two parts. When the water contents in substrate were added with sodium chloride solution in cotton waste box cultivation as a first experiment, the growth of mushroom was damaged as the concentration was increased, even though there was a little difference according to the strains. The yield in 1.0% NaCl solution was decreased to 72% compared to non-treated plot while that in 3.0% solution was only 2% of the non-treated plot. Morphological characteristics of mushrooms cultivated in substrate with the different concentration of the solution showed different results. For example, the size and thickness of pilei were not influenced by NaCl concentration, but the length of stipes and individual weight were much influenced. In plastic box cultivation filled with cotton waste, watering treatment with the different concentrations of sodium chloride solution, the second experiment, did not show any difference according to the concentration until 1.0% solution but there was a little difference according to the strains. The productivity of fruitbody started to decrease at 2.0% of the solution and the yield and quality of mushroom in 3.0% solution treatment were generally low. After the second flush, days for mushroom sprouting were generally prolonged in proportion to the solution concentration. Taken altogether, the second experiment did not show a clear effect as the case of the first experiment.

• Research in Plant Disease
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• v.25 no.1
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• pp.8-15
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• 2019

Plum pox virus (PPV) is a significant viral disease in Prunus spp. worldwide. A nationwide survey was started in Prunus spp. orchards, since PPV was first detected from peach in Korea, 2015. During 2016-2017, samples were collected from 30,333 trees in 1,985 orchards of stone fruits in 8 provinces and 4 cities, Korea and tested by RT-PCR using specific PPV primer set. As a result, 21 trees including peach (9 trees), Japanese apricot (4 trees), plum (1 tree), apricot (7 trees) in 10 orchards were infected and controlled by eradication program. Amplicons of the expected size (547 bp) were obtained from total RNA of seven peach trees in 2016, and directly sequenced. BLAST analysis revealed the highest nucleotide (NT) identity (99%) with a PPV D isolates (LC331298, LT600782) in Genbank. The seven isolates from shared nt sequence identities of 98 to 100% with one another. Phylogenetic analysis showed the isolates in peach clustered closely with the PPV-D isolates from Korea, Japan, USA, and Canada. This is, to our knowledge, the first report of the presence of PPV in Prunus spp. orchards in Korea, 2016-2017, we hope that our results and efforts will contribute to effective measures for eradication of PPV.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Korean Academy of Nursing
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• v.7 no.2
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• pp.43-59
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• 1977

The Community Health Service considers the family as a service unit and places the emphasis of its service on the health problems and the nursing needs of the family rather than the individual. From the conceptual point of view that tile community health service is both health maintenance and health promotion of the family, the community health nurse should have a knowledge of the growth and development of the family and be responsible for the comprehensive support of normal family development. The community health nurse often is in a position to make a real contribution to normal family development. In order to investigate the relationship between the areas of nursing need and family development, the following objectives were established 1. To discover the general characteristics of the study population by the stage of family development. 2. To discover specific nursing needs in relation to the family developmental stage, and to determine the intensity of the nursing needs and the ability of the family to cope with these needs. 3. To discover overall family health nursing problems in relation to the family developmental stage and determine the intensity of the nursing need and the problem solving ability of family. Definitions : The family developmental stages as classified by Dually were used stage 1. Married couples(without children) stage 2. Childbearing Families (oldest child birth to 30 months of age) stage 3. Families with preschool children (oldest child 2½-to 6 years) stage 4. Families with schoolchildren (oldest child 6 to 13 years). stage 5. Families with teenagers (oldest child 13 to 20 years) stage 6. Families as launching centers (first child gone to last child′s leaving home). stage 7. Middle- aged parents (empty nest to retirement) stage 8. Aging family member (retirement to death of both spouses) The areas of nursing need were defined as those used in the study, "A Comprehensive Study about Health and Nursing Need and a Social Diagram of the Community", by tile Nursing research Institute and Center for population. and Family Planning, July 1974. The study population defiled and selected were 260 nuclear families ill two myron of Kang Hwa Island. Percent, mean value and F- test were utilized in tile statistical analysis of the study result. Findings : 1. General characteristics of the study population by tile family developmental stage ; 1)The study population was distributed by the family developmental stage as follows : stage 1 : 3 families stage 2 : 13 families stage 3 : 24 families stage 4 : 41 families stage 5 : 50 families stage 6 : 106 families stage 7 : 13 families stage 8 : 10 families 2) Most families had 4 or 5 members except for those in stage, 1, 7, and 8. 3) The parents′ present age was older in the higher developmental stage and their age at marriage was also younger in the higher developmental stages. 4) The educational level of parents was primarily less than elementary school irrespective of the developmental stage. 5) More than half of parents′ occupations were listed as laborers irrespective of the developmental stage, 6) More than half of the parents were atheists irrespective of the developmental stage. 7) The higher the developmental stage(from stage 2 to stage 6 ), the wider the distribution of children′s ages. 8) More than half of the families were of middle or lower socio-economic level. 2. Problems in specific areas of nursing need by family developmental stage, the intensity of nursing need and the problem solving ability of the family : 1) As a whole, many problems, irrespective of the developmental stage, occurred in tile areas of Housing and Sanitation, Eating Patterns, Housekeeping, Preventive Measures and Dental care. Problems occurring ill particular stages included the following ; stage 1 : Prevention of Accident stage 2 : Preventive Vaccination, Family Planning. stage 3 : Preventive Vaccination, Maternal Health, Family Planning, Health of Infant and Preschooler. stage 4, 5 : Preventive Vaccination, Family Planning, Health of School Children. stage 6 : Preventive Vaccination, Health of School Children. 2) The intensity of the nursing need in the area of Acute and Chronic Diseases was generally of moderate degree or above irrespective of the developmental stages except for stage 1. Other areas of need listed as moderate or above were found in the following stages: stage 1 : Maternal Health stage 3 . Horsing and Sanitation, Prevention of Accident. stage 4 . Housing and Sanitation. stage 5 : Housing and Sanitation, Diagnostic and Medical Care. stage 6 : Diagnostic and Medical care stage 7 : Diagnostic and Medical Care, Housekeeping. stage 8 : Housing and Sanitation, Prevention of Accident, Diagnostic and Medical Care, Dental Care, Eating Patterns, Housekeeping. 3) Areas of need with moderate problem solving ability or less were as follows : stage 1 : Diagnostic and Medical Care, Maternal Health. stage 2 : Prevention of Accident, Acute and Chronic Disease, Dental Care. stage 3 : Housing and Sanitation, Acute and Chronic Disease, Diagnostic and Medical Care, Preventive Measure, Dental Care, Maternal Health, Health of Infant and preschooler, Eating Patterns. stage 4 : Housing and Sanitation, Prevention of Accident, Diagnostic and Medical Care, Preventive Measure, Dental Care, Maternal Health, Health of New Born, Health of Infant and Preschooler, Health of school Children, Eating Patterns, Housekeeping. stage 5 . Housing and Sanitation, Prevention of Accident, Acute and Chronic Disease, Diagnostic and Medical Care, Preventive Measure, Dental Care, Preventive Vaccination, Maternal Health, Eating Patterns. stage 7, 8 : Housing and Sanitation, Prevention of Accident, Acute and Chronic Disease, Diagnostic and Medical Care, Preventive Measures, Dental Care, Preventive Vaccination, Eating Patterns , Housekeeping. Problem occurrence, the degree of nursing need and the degree of problem solving ability 1 nursing need areas for the family as a whole were as follows : 1) The higher the stages(except stage 1 ), the lower the rate of problem occurrence. 2) The higher the stage becomes, the lower the intensity of the nursing need becomes. 3) The higher the stages (except stages 7 and 8), the higher. the problem solving ability. Conclusions ; 1) When the nursing care plan for the family is drawn up, depending upon the stage of family development, higher priority should be give to nursing need areas ① at which problems were shown to occur ② where the nursing need is shown to be above moderate degree and ③ where the problem solving ability was shown to be of moderate degree. 2) The priority of the nursing service should be Placed ① not on those families in the high developmental stage but on those families in the low developmental stage ② and on those areas of need shown in stages 7 and 8 where the degree nursing need was high and the ability to cope low.

• Korean Journal of Weed Science
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• v.16 no.4
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• pp.264-281
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• 1996

As a consequence of wide use of herbicides, Eleocharis kuroguwai Ohwi became a dorminant problem weed for rice cultivation in Korea. To understand the establishment of the weed, experiments on physio-ecological characteristics were carried out sprouting and occurrence, the results could be summarized as follows: Sprouting percentage remained 68 to 73% until the time of field emergence, indicating many of the them are still dormant. The proportion of the dormant tubers were greater for the smaller than the bigger tubers. Apical dominance was apparent in sprouting, with 84% of tuber sprouted from only one of the apical buds. Tubers sprouted from 2 or 3 buds were less than 20%, and were mostly from the bigger tubers. When the shoot growth was compared, by controlling the others, ones from apical and the next 3 buds showed similar vigorous growth, but the later ones showed poorer growth. For the longevity of tubers, deep soil storage appeared to be better than storage in temperature controlled room to 2~$3^{\circ}C$. Emergence of E. kuroguwai was better in clay soil than in sand, and the possible depth for emergence in clay soil appeared to be up to 21cm, but was 15cm in sand. When tubers were exposed to salt solutions before emergence tests, E. kuroguwai appeared to be much sensitive to salts than S.planiculmis. Among the tubers formed in previous year, 12.7% remained still viable until the end of next crop season, but with relatively strong dormancy. The first emergence was about 10 days after planting at ordinary cropping seasons, and the days to the maximum shoot number stage were 60~90 from planting. The duration was extended at early transplanting, and shoot number, leaves per shoot, and tubers developed per plant were also greater at early plantings. The 6th order offshoots were developing when E. kuroguwai was planted at early season. When planted at later seasons, generation and the number of offshoots was reduced planted at early season. When planted at later seasons, generation and the number of offshoots was reduced and the number of tubers, runner and rhizome lengths was also reduced.

• 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.