• Journal of Internet Computing and Services
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• v.25 no.5
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• pp.31-40
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• 2024

Aortic valve stenosis is disease caused by the calcification of the aortic valve, which is located between the left ventricle of the heart and the aorta, preventing the backflow of blood. Transcatheter Aortic Valve Replacement (TAVR) has become the standard non-surgical procedure for treating aortic stenosis. However, patients who undergo TAVR are still face the risk of complication, which calls for a systematic solution for complication prediction and management. In this study, we designed a platform that manages patient complication risks using various prediction models, and we utilized explainable AI to ensure reliable prediction models and solutions. For the implementation of this platform, digital twin technology was employed, allowing for complication prediction and monitoring based on a patient's digital twin model constructed from Real-World Data (RWD). The digital twin platform has been developed with a microservice architecture using Kubernetes, enhancing the flexibility and availability of the platform. Additionally, we propose a feedback system for continuous improvement of prediction model performance and TAVR procedures to ensure ongoing development.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.500-503
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• 2002

Biomedical signals are ubiquitously contaminated and degraded by background noise which span nearly all frequency bandwidths. This paper proposes the MADF (multiplication free adaptive digital filter) algorithm to cancel the noise. And the convergence characteristics of the algorithm is analyzed. In the experimental results, the MADF algorithm has the advantage in which has superior to a condition of low-frequency and slow data speed. This application gives an important significance in ensuring the objectivity of clinical information and in promoting the representation and the disease diagnosis.

• Journal of Korean Medical classics
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• v.23 no.4
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• pp.31-33
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• 2010

The earliest record of 'Eum-yang Interlocking(陰陽交)' is in "Hwangjenaegyeong(黃帝內經)". In this article, we reviewed the meaning of the two Chinese Characters 'On'(溫) and "Gyo"(交), discussed the meaning, mechanism and treatment principles of Eum-yang Interlocking and Three Incurable Symptoms in order to provide a theoretical basis for treating the warm febrile disease in modern times.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.303-310
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• 2012

In order to analyze factors that support effective health care delivery system, this study aimed to research general public's perception on the functions of medical institutions(based on the levels of treatment: primary care, secondary care, and tertiary care), choices of medical institution when contracted with an unfamiliar disease, and recognition of diseases based on their severities. We collected data using self-administered survey from 400 general public living in Seoul, S. Korea from April 25 to May 18, 2011. The analysis was conducted using frequency analysis, chi-square test, and t-test; we analyzed the data to see if there are differences based on gender, age, and level of education. The result of both recognition of functional differences of medical institutions and selection of medical institutions when contracted with unfamiliar diseases showed that there were no significant differences based on the gender; however there were significant differences when considering the age and education. Looking at the result of the knowledge of the disease classification based on its severity, there were significant differences in age, gender, and education. In order to provide sustainable and effective health care delivery system, utilization of primary care as well as education and promotion regarding the functional differences of medical institutions and classification of disease based on its severity need to be encouraged.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.279-291
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• 2018

This study is designed to demonstrate risk factors of unmet medical care for people with cerebrovascular disease. To do this, statistical analysis was performed by using hierarchical logistic regression analysis with SPSS/WIN24.0 program using Korean Medical Panel data in 2014. In the final model of the hierarchical logistic regression analysis, which is based on Anderson's Model, adjusted for the factors of the predisposing and enabling factors, the explanatory variables affecting the unmet medical development are gender, economic activity, income level, the experience of lying in a sickbed, restriction on activity, subjective health condition, and the number of chronic diseases. Based on the results of this study, the practical and policy implications for the effective management and treatment of cerebrovascular disease should be included in the countermeasures for cerebrovascular disease, a strategy to reduce the unmet medical incidence of cerebrovascular disease, in order to meet the medical needs, the necessity of comprehensive measures considering various dimensions of variables and the influential variables of unmet medical emergence have been suggested for the necessity of making a detailed service manual that can improve accessibility to medical services.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.509-521
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• 2016

A novel Samples Balanced Genetic Algorithm combined with Extreme Learning Machine (SBGA-ELM) for Parkinson's Disease diagnosis and detecting bio-markers is presented in this paper. Proposed approach uses genes' expression data of 22,283 genes from open source ParkDB data base for accurate PD diagnosis and detecting bio-markers. Proposed SBGA-ELM includes two major steps: feature (genes) selection and classification. Feature selection procedure is based on proposed Samples Balanced Genetic Algorithm designed specifically for genes expression data from ParkDB. Proposed SBGA searches a robust subset of genes among 22,283 genes available in ParkDB for further analysis. In the "classification" step chosen set of genes is used to train an Extreme Learning Machine (ELM) classifier for an accurate PD diagnosis. Discovered robust subset of genes creates ELM classifier with stable generalization performance for PD diagnosis. In this research the robust subset of genes is also used to discover 24 bio-markers probably responsible for Parkinson's Disease. Discovered robust subset of genes was verified by using existing PD diagnosis approaches such as SVM and PBL-McRBFN. Both tested methods caused maximum generalization performance.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.353-366
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• 2015

The purpose of this study was to examine how region-specific characteristics affect the occurrence of cardiac arrest. To analyze, we combined a unique data set including key indicators of health condition and cardiac arrest occurrence at the 244 small administrative districts. Our data came from two main sources in Korea Center For Disease Control and Prevention (KCDC): 2010 Out-of-Hospital Cardiac Arrest Surveillance and Community Health Survey. We analyzed data by using multiple regression, geographically weighted regression and decision tree. Decision tree model is selected as the final model to explain regional variations of cardiac arrest. Factors of regional variations of cardiac arrest occurrence are population density, diagnosis rates of hypertension, stress level, participating screening level, high drinking rate, and smoking rate. Taken as a whole, accounting for geographical variations of health conditions, health behaviors and other socioeconomic factors are important when regionally customized health policy is implemented to decrease the cardiac arrest occurrence.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.317-330
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• 2020

The purpose of this study was to compare lifestyle, dietary habit, health attitude and self-efficacy among chronic schizophrenia with upper gastrointestinal disease and chronic schizophrenia to improve lifestyle, dietary habit and health attitude, in each mental health care facilities field, it was attempted to provide basic data to search for alternatives to increase self-efficacy. This study surveyed them from February 20^th to April 30^th in 2019 for data collection. Data were analyzed using Chi-square test, Independent t-test and ANCOVA with SPSS/WIN 22.0. The sociodemographic factor of age and education, the lifestyle factors of carbonated drink and physical activity intensity, the dietary habit factors of overeat, snack, late night meals and fatty food, the other factor of self-efficacy show statistically significant differences among groups. The study provides meaningful data in finding distinctive features of Upper Gastrointestinal Disease among Group with Chronic Schizophrenia. The results indicate that need to develope a variety of intervention methods to promote lifestyle and dietary habit and to enhance self-efficacy of chronic schizophrenia.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.909-918
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• 2022

The aim of this study is to explore the day care center administrators' educational needs and self-efficacy in prevention of infectious diseases and identify the factors affecting the self-efficacy in preventing infectious disease. The participants were 172 day care center administrators in G, J, S City, data was collected using self report questionnaires. The data was analyzed with descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, Multiple regression analysis using SPSS 24.0. Educational needs of infectious disease 'When and how to hand wash', 'Method to clean and disinfect' were high and self-efficacy in prevention of infectious diseases on hand washing education and time were high. And there was a positive correlation between educational needs and self-efficacy in prevention of infectious diseases (r=.528, p<.001). The factors affecting self-efficacy in prevention of infectious diseases were the educational needs for the prevention of infection (β=.53, p<.001) and experience in infection prevention education (β=.25, p<.001). This study showed that it is necessary to develop and apply programs that can meet the Educational need of infectious disease for day care center administrators. Through such education, the self-efficacy in prevention of infectious diseases of participants can be improved.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.243-252
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• 2018

The purpose of this study was to examine relationships among disease-related characteristics, symptom stress, quality of life in women with endometriosis, and then to identify predictors of quality of life in them. The self-reported questionnaires were administered to 99 women in one general hospital. As results of multiple regression analysis, the factors affecting quality of life in women with endometriosis were sick leave (${\beta}=-.27$, p=.000) and symptom stress (${\beta}=.59$, p=.000), explained women's quality of life with 57.0% (F=11.39, p<.001). Based on the findings, there is a need to develop a self-care program for chronic pain and a nursing intervention for enhancing a quality of life in women with endometriosis.