• Journal of Physiology & Pathology in Korean Medicine
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• v.16 no.2
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• pp.279-288
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• 2002

This research investigates the effect of the Crataegus pinnatifida BGE. var. major N.E. BR(CPVM) on Alzheimer's disease. The CPVM extract suppressed the expression of IL-1 β, IL-6, APP, AChE mRNA in PC-12 cells treated with CT105. The CPVM extract suppressed the AChE activity, and the production of APP significantly in PC-12 cells treated with CT105. The CPVM extract group showed a significant inhibitory effect on the memory deficit for the mice with Alzheimer's disease induced by CT105 in the Morris water maze experiment. The CPVM extract suppressed the over-expression of IL-1 β, TNF- α and ROS in the mice with Alzheimer's disease induced by CT105. This study suggests that CPVM may be effective for the prevention and treatment of Alzheimer's disease.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.233-238
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• 2017

Automatic identification of disease in plants from their leaves is one of the most challenging task to researchers. Diseases among plants degrade their performance and results into a huge reduction of agricultural products. Therefore, early and accurate diagnosis of such disease is of the utmost importance. The advancement in deep Convolutional Neural Network (CNN) has change the way of processing images as compared to traditional image processing techniques. Deep learning architectures are composed of multiple processing layers that learn the representations of data with multiple levels of abstraction. Therefore, proved highly effective in comparison to many state-of-the-art works. In this paper, we present a plant disease identification methodology from their leaves using deep CNNs. For this, we have adopted GoogLeNet that is considered a powerful architecture of deep learning to identify the disease types. Transfer learning has been used to fine tune the pre-trained model. An accuracy of 85.04% has been recorded in the identification of four disease class in Apple plant leaves. Finally, a comparison with other models has been performed to show the effectiveness of the approach.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.817-827
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• 2017

Purpose: This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease. Methods: This was a secondary analysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at a university medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplus version 7.4 for latent class analysis. Results: Four latent classes of risk factors for coronary artery disease were identified in the final model: 'smoking-drinking', 'high-risk for dyslipidemia', 'high-risk for metabolic syndrome', and 'high-risk for diabetes and malnutrition'. The likelihood of these latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation. Conclusion: The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpful data to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulation should be considered during the development of interventions.

• Journal of Korean society of Dental Hygiene
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• v.21 no.5
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• pp.575-583
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• 2021

Objectives: This study aimed to investigate the relationship between sleep quality and periodontal disease-related symptoms among Korean adolescents. Methods: This cross-sectional study was based on the 16th Korea Youth Risk Behavior Web-Based Survey (2020). A complex sample logistic regression was performed to identify the relationship between sleep quality and periodontal disease-related symptoms after adjusting for all covariates. Results: In model II, to estimate the adjusted odds ratio (AOR) for all covariates, students who answered "not at all sufficient", indicating sleep quality, were at higher risk of experiencing periodontal disease-related symptoms than those who answered "completely sufficient" (AOR=1.58). As a result of subgroup analysis, for estimating the AOR adjusted for all covariates in boys, students who answered "not at all sufficient", indicating sleep quality, were at a higher risk of experiencing periodontal disease-related symptoms than those who answered "completely sufficient" (AOR=1.68). In girls, students who answered "not at all sufficient", indicating sleep quality, were at a higher risk of experiencing periodontal disease-related symptoms than those who answered "completely sufficient" (AOR=1.43). Conclusions: It is necessary to formulate health policies that can promote optimal sleeping habits and oral health behaviors among Korean adolescents.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.185-192
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• 2012

Globally, U-health services have been increased according to the increase in interests on health managing and the development of information communication technology (ICT) based on increases in advanced ages and chronic disease. Exiting U-health services provide required services and health information monitoring only through counsels and that represent limitations in preventing and managing cardiovascular disease patients like chronic patients. In this paper, we propose of U-health platform based health management service model using context information. In our service model can provide health monitoring, diet, and exercise service using context information of clinical information and wether in U-health platform environment. Service to offer is the specialized service using external content provider of DB. in addition to, doctor can to provide advice information to patient using monitoring service. The proposed service model provides effective services using context information in U-health platform environments to customers and that will improve the health of chronic patients.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.107-111
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• 2006

According to IT(information technology) industry progress. our life is gradually convenient. The proliferation of environmental pollution and the threat of diseases proportional to the progress comes to be high gradually. We must prevent dangerous diseases which threatens the life of the human. Or we are bumped against irrevocable serious situation. In spite of the situation. managing one's own health against modern busy lifestyle is very difficult. Therefore, we need to manage our health situation by using sensors based on ubiquitous IT environment. In this paper. we propose a diagnostic model which is able to diagnose and prevent a cerebrovascular disease based on ubiquitous technology. Also. as a step of implementing the u-health care diagnosis system, the diagnosis model of cerebrovascular disease plays an important role to decide a clinic result. In the future, by using this model. we may improve our welfare and health.

• Korean Journal of Health Education and Promotion
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• v.9 no.2
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• pp.103-120
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• 1992

The purpose of this study was designed for the model development of curriculum of school health education including learning-teaching method, through analysis of results compared between a regular schedule health instruction and irregular health education. And this study is an attempt to give fundamental information for establishing of school health subject as the concept and scope of the school health subject is still not recognized and accepted satisfactorily in Korea. The data were collected by questionnaire from middle school girls and were carried out from 1989 to 1991. The major results obtained from this study were as follows: A Analysis of the case of school health. instruction 1. The responses of students about health eaducation : The positive rate of answers on the 'Health education is very important subject' was 91.2%, and on the 'I can maintain well healthful life : int of selfcare' was 87.1%. 2. The condition on knowledge, attitude and practice about health education: Education group had higher scores than comparison group about all most of questions, especially sex-education and drug abuse prevention education. 3. All the case of disease early founded out during the health instruction were children disease such as bone-tumor, lymphoma, hydrocephalus, and leukemia. B. Model development of school health education 1. Component of the health education subject (1) Healthful Life → Personal Health (2) Physical anatomy and Prevention of disease → Community Health (3) Growth and Development(sex education) → Community Health (4) Environment and Health → Community Health (5) Previntion of drug abuse → Human Health (6) Safety life → Human Health 2. Leanning - teaching method of health instruction (1) A Model of leaning-teaching method : A regular circulating health instruction by the component health subject for 2 hours a month. (2) B Model of leaning-teaching method : A regular schedule health education for hour a week.

• Korea journal of population studies
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• v.8 no.2
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• pp.46-67
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• 1985

In this paper, an attempt has been made to examine the pattern of mortality in Korea during 1970~80. By applying the age-sex specific mortality rates quoted from 1978~79 life tables for Korea published by NBOS, EPB to those of the West pattern of regional model life tables and the far eastern pattern of model life tables for developing countries, life expectancy at birth were calculated. Also the author reviewed the trends of death rates, life expectancy and cause of death using vital registration data and other materials. Summarized results are as follows; 1. Crude death rates in Korea was reduced to one fifth in the 1983 compared to that in 1920's. Life expectancy also improved to almost double in 1985 compared to 1920's. But the difference in the life expectancy between male and female increased during that period and it was recorded as 6.4 years in 1985. This discrepancy was mainly due to the different tempo of decreasing in mortality level by sex, particularly, for the age 40 and above. 2. For the pattern of mortality in Korea, it showed that female mortality could accounted closer to the West pattern model life tables. There were high similarity between actual pattern prevalent in Korea and West pattern. And its coefficient of variance was also very low. However for the case of male, it was difficult to find the exact model life tables for explaining the actual situation on the male mortality pattern which means exist considerable dissimilarity in older ages. The Far eastern pattern of U.N. model life tables show better results than West pattern, however, the deviation of the pattern to actual was severe. Also in Far eastern pattern, high coefficient of variance was existed. Furthermore it was found in the paper that the mortality level of Korean male for the age 40 and above were much higher than that of Far eastern pattern which was reflected the high mortality of the male adult in Far east region. 3. The analysis of cause of death showed that circulatory disease such as cerebrovascular disease and hypertensive disease accounted for the leading cause of death in Korea for the age 40 and above. There should he paid special attention to chronic retrogressive diseases for the older age groups. For younger age groups, injury and poisoning were reported as important cause of death.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• Journal of Veterinary Science
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• v.23 no.3
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• pp.41.1-41.15
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• 2022

Background: Proliferative enteritis caused by Lawsonia intracellularis undermines the economic stability of the swine industry worldwide. The development of cost-effective animal models to study the pathophysiology of the disease will help develop strategies to counter this bacterium. Objectives: This study focused on establishing a model of gastrointestinal (GI) infection of L. intracellularis in C57BL/6 mice to evaluate the disease progression and lesions of proliferative enteropathy (PE) in murine GI tissue. Methods: We assessed the murine mucosal and cell-mediated immune responses generated in response to inoculation with L. intracellularis. Results: The mice developed characteristic lesions of the disease and shed L. intracellularis in the feces following oral inoculation with 5 × 10⁷ bacteria. An increase in L. intracellularis 16s rRNA and groEL copies in the intestine of infected mice indicated intestinal dissemination of the bacteria. The C57BL/6 mice appeared capable of modulating humoral and cell-mediated immune responses to L. intracellularis infection. Notably, the expression of genes for the vitamin B12 receptor and for secreted and membrane-bound mucins were downregulated in L. intracellularis -infected mice. Furthermore, L. intracellularis colonization of the mouse intestine was confirmed by the immunohistochemistry and western blot analyses. Conclusions: This is the first study demonstrating the contributions of bacterial chaperonin and host nutrient genes to PE using an immunocompetent mouse model. This mouse infection model may serve as a platform from which to study L. intracellularis infection and develop potential vaccination and therapeutic strategies to treat PE.