• 보건의료산업학회지
• /
• 제6권3호
• /
• pp.29-38
• /
• 2012

The aim of this study was to examine the spouse effects on depressive symptom and suicidal thinking among the elderly aged 65 and over in Korea. The subjects selected from the database of the Fourth Korea National Health and Nutrition Examination Survey(KNHANES IV) conducted by Korea Centers for Disease Control and Prevention from 2007 to 2009. Those who were female, older, lower educated, or poorer were more likely to live alone than their counterparts respectively. The elderly living alone experienced depressive symptom as 2.0 times(OR=2.004, 95% CI=1.433, 2.803) as, and suicidal thinking as 1.6 times(OR=1.567, 95% CI=1.111, 2.211) as the elderly couples did, adjusting for socio-economic factor, health status factors, and health behaviors factors. As for the male subgroup, the elderly living alone experienced depressive symptom as 4.0 times(OR=3.997, 95% CI=2.066, 7.732) as, and suicidal thinking as 3.2 times(OR=3.181, 95% CI=1.535, 6.592) as the elderly couples did. On the other hands, there was no significant difference in depressive symptoms and suicidal thinking between the female elderly living alone and couples. The authors suggested policy interventions to promote the mental health of the male elderly living alone.

• 대한치과기공학회지
• /
• 제35권2호
• /
• pp.157-171
• /
• 2013

Purpose: This study aims to present a database for the development of a healthcare management program based on the survey and analysis of self reported psychosomatic symptoms among the current dental technology students. Methods: Subjects of our study are 480 dental technology major students enrolled in a third year college located Gyeonggi, Chungcheong, and Gangwon province. Using a random sampling, we conducted a self-report survey from August 30, 2011 to October 28, 2011 and 418 reports were collected as feedback and we put an analysis on them. Results: 1. The average physical self symptom was 20.49, which is higher than the average mental self symptom(18.54). Of the subcategories of psychosomatic self symptom, we observed multiple subjective symptoms as the highest one(37.77), and aggression as the lowest(13.77). 2. As to gender, both physical and mental self symptom were statistically significant with the scale score of(p<.001). The scale score of subcategories is as follows; multiple subjective symptoms(I, p<.001), eye and skin(B, p<.001), digestive(C, p<.001), impulsiveness(H, p<.001), lie scale(L, p<.001), mental instability(J, p<.001), depression(K, p<.001), aggression(F, p<.001), irregularity of life(G, p<.001), mouth and anal(D, p<.05), nervousness(E, p<.05). 3. As for obesity, statistical significance was shown with the scale scores of physical self symptom(p<.001), multiple subjective symptoms(I, p<.001), digestive(C, p<.001), aggression(F, p<.001), depression(K, p<.01), irregularity of life(G, p<.01), respiratory(A, p<.05), eye and skin(B, p<.05), impulsiveness(H, p<.05), mental instability(J, p<.05). The scale scores in the environmental quality and life satisfaction were shown as follows; depression(K, p<.001), lie scale(L, p<.01), and irregularity of life(G, p<.05). 4. We employed multiple regression analysis to take account of general factors affecting psychosomatic self symptoms, and drew that the explanatory power of the model was proved with the scales of physical self symptom(4.1%) and mental self-symptom(3.6%). Obesity was a factor that affects physical self symptom with the scale score of(p<.01), and environmental quality and life satisfaction(p<.01) and obesity(p<.05) affect mental self symptom. Conclusion: In this analysis we observed obesity of dental technology students can influence their psychosomatic self symptoms. In this sense, it would be reasonable to develop a healthcare management and education programs that help the students maintain a healthy weight and promote their health.

• 대한예방한의학회지
• /
• 제17권2호
• /
• pp.179-187
• /
• 2013

Objectives : In many cases, patient's symptoms have been recorded on EMR in natural language instead of medical terminologies. It is possible to build a database by analyzing the symptoms of Korean Medicine(KM) that indicates patient's symptoms in natural language. Using the database, when doctors record patient's symptoms on EMR in natural language, conversely it'll be also possible to extract the symptoms of KM from those natural language. The database will enhance the value of EMR as a medical data. Methods : In this study, we aimed to make data structure of the terminologies that represent the symptoms of KM. The data structure is combinations of smallest unit in natural language. We made the database by analyzing morpheme of the natural language to express the symptoms of KM. Results & Conclusions : By classifying the natural language in 15 features, we made the structure of concept and the data available for morphological analysis.

• International journal of advanced smart convergence
• /
• 제7권4호
• /
• pp.1-9
• /
• 2018

With developments in science and technology and improvement in living standards, human life expectancy is steadily increasing worldwide. For effective healthcare, it is necessary to check health conditions according to individuals' behavior and acquire prior knowledge on possible diseases. In this study, we classified the diseases that are major causes of death in Korea by referring to data provided by the Korea National Health and Nutrition Examination Survey. We selected indexes that could be used as indicators of major diseases and created the LCBB-SC. In the LCBB-SC, the data are systematically subdivided into related fields to provide integrated data related to each disease and to provide an infrastructure that can be used by researchers. In addition, by developing a web interface allowing for self-symptom assessments, this resource will be beneficial to people who want to check their own health condition using a list of diseases that might be caused by their behaviors.

• Journal of information and communication convergence engineering
• /
• 제15권2호
• /
• pp.85-90
• /
• 2017

Expert systems for health diagnosis are only for medical experts who have deep knowledge in the field but we need a self-checking pre-diagnosis system for preventive public health monitoring. Korea Traditional Medicine is popular in use among Korean public but there exist few available health information systems on the internet. A computerized self-checking diagnosis system is proposed to reduce the social cost by monitoring health status with simple symptom checking procedures especially for Korea Traditional Medicine users. Based on the national reports for disease/symptoms of Korea Traditional Medicine, we build a reliable database and devise an intelligent inference engine using fuzzy c-means clustering. The implemented system gives five most probable diseases a user might have with respect to symptoms given by the user. Inference results are verified by Korea Traditional Medicine doctors as sufficiently accurate and easy to use.

• Nuclear Engineering and Technology
• /
• 제36권3호
• /
• pp.219-228
• /
• 2004

[1] and [2] present an approach to diagnosing possible defects in the mechanical systems of a nuclear power plant. In this paper, by using a fault library as a database and training data, we develop a diagnostic algorithm 1) to decide whether an Air Operated Valve system is sound or not and 2) to identify the defect from which an Air-Operated Valve system suffers, if any. This algorithm is composed of three stages: a neural net stage, a non-neural net stage, and an integration stage. The neural net stage is a simple perceptron, a pattern-recognition module, using a neural net. The non-neural net stage is a simple pattern-matching algorithm, which translates the degree of matching into a corresponding number. The integration stage collects each output and makes a decision. We present a simulation result and confirm that the developed algorithm works accurately, if the input matches one in the database.

• 융합정보논문지
• /
• 제10권8호
• /
• pp.15-22
• /
• 2020

4차 산업 혁명과 데이터 환경의 급격한 변화는 기존 관계형 데이터베이스(RDB)는 기술적 한계를 드러내고 있다. IDC/금융/보험 등 전 분야에서 비정형 데이터에 대한 새로운 분석방안으로 그래프 데이터베이스(GDB) 기술에 관심이 높아지고 있다. 그래프 데이터베이스는 상호 연동된 데이터를 표현하고 광범위한 네트워크에서 연관 관계 분석에 효율적인 기술이다. 본 연구는 기존 RDB를 GDB 모델로 확장하고, 새로운 이상징후 탐지를 위해 기계학습 알고리즘(패턴인식, 클러스터링, 경로거리, 핵심추출)을 적용하였다. 성능분석 결과 이상 행위 성능(약 180배 이상)이 크게 향상되었고, RDB로 분석 불가능한 5단계 이후 이상징후 패턴을 추출할 수 있음을 확인하였다.

• 대한한의학원전학회지
• /
• 제32권3호
• /
• pp.131-146
• /
• 2019

Objectives : The aim of this paper is to study the methodology for effectively analyzing the "Jinguiyaolue" prescriptions using database, and to explore possibilities of applying the data construction and query produced in the process to comparative research with other texts in the future. Methods : Using "Xinbianzhongjingquanshu(新編仲景全書)" as original script, the contents of "Jinguiyaolue" were entered into the database, in which one verse would be separated according to content for individual usage. Also, data with medicinal construction and disease pattern information of the previously constructed "Shanghanlun" database designed for comparison with other texts was applied for comparative analysis. Results : For input and analysis, 6 tables and 12 queries were made and used. Formulas were accessible by using herbal combinations, and applications of these formulas could be assembled for comparison. Formulas were also accessible by using disease pattern combinations, and combinations of herbs and disease pattern together were also applicable. In comparison with other texts, examples and frequency of usage of herbs could be relatively accurately compared, while disease patterns could not easily be compared. Conclusions : Herbal combinations, disease pattern combinations could yield related texts and herb/disease pattern combinations of the prescriptions in the "Jinguiyaolue", which shortened time needed for research among formulas in texts. However, standardization research for disease pattern is necessary for a more accurate comparative study that includes disease pattern information.

• 성인간호학회지
• /
• 제28권2호
• /
• pp.213-225
• /
• 2016

Purpose: The purpose of this study was to provide basic data about agitation in patients with dementia by surveying the literature. Method: Key words used for search through hand-search and electronic database (CINHAL, Pubmed, Google scholar, Riss, Kiss, DBpia) included 'dementia', 'Alzheimer disease', 'agitation', 'aggression or aggressive behavior', 'problem or disruptive behavior', and 'abnormal behavior.' Seventeen studies met the inclusion criteria for the Meta-analysis and 'R' version 3.2.2 was used to analyze the correlated effect size. Results: Study results showed that variables related to agitation were identified as the demographic (age, gender), dementia-related (cognition, medication uses), physical (Activity of Daily Living [ADL], pain), psychological (depression, psychotic symptom, caregiver burden) and environmental (psychosocial environment) factors. The effect size between the correlated variables and agitation were low to moderate (caregiver burden .36; ADL -.24; psychotic symptom and depression .21; pain .19; cognition -.15; medication uses .12; and psychosocial environment -.12). Conclusion: Based on the findings of this study, strategies to improve patients' depressive and psychotic symptoms and ADL and to reduce caregivers' burden are needed for prevention and management of agitation in patients with dementia.

• 한국조리학회지
• /
• 제21권4호
• /
• pp.251-270
• /
• 2015

본 연구의 목적은 한국 고유의 전통지식에 기반하여 음식을 이용한 건강증진 방법에 대한 지식을 체계화하고 통계적으로 활용할 수 있는 방법에 대하여 연구하는 데 있다. 이를 위하여 한국 고유의 음식을 이용한 질병치료에 대하여 언급한 고문헌인 식료찬요(食療纂要)의 지식을 DB로 구축하였다. 데이터의 처리는 Relational Data Model을 이용하였고, 9개의 데이터 테이블을 사용하였다. 소프트웨어는 MS사의 Access 2014를 사용하였다. 그 결과, 데이터베이스 쿼리문장을 이용하여 식재료, 약재별, 증상, 병명, 효능, 변증 정보를 유기적으로 조건을 만들어 통계적 결과를 즉시 확인할 수 있었다. 따라서 이러한 Relational Data Model을 이용하여 기존 방식의 연구논문을 대체할 수 있었다.