• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2010년도 제42차 하계학술발표논문집 18권2호
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• pp.183-186
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• 2010

유비쿼터스 환경에 대한 기술적 발전에 따라 다양한 u-Health 서비스 시스템이 개발되어 시행되고 있다. u-Health 시스템은 서비스 인프라인 병원, 의료기관의 의료정보시스템 연동을 통한 의료정보활용이 불가피하다. 그러나 HL7 의료정보 표준안은 헬스케어 시스템에서 활용하는 의료정보에 대한 명세를 제시하지 못하고 있다. 즉 의료정보시스템으로부터 정보를 요청/제공 받기 위한 HL7 표준 메시지가 명시되어 있지 않다. 따라서 본 논문에서는 헬스케어 시스템에서 필요로 하는 병원 내 의료정보를 분석하고 적합한 HL7 표준 메시지 구조를 설계하였다.

• Korean Journal of Health Education and Promotion
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• 제1권1호
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• pp.43-57
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• 1999

One of the most fundamental and the oldest issues in the provision of health care throughout the world has been the issue of the role of the public and private sector of health care, and the relationship between them. This paper describes issues associated with the concept of health oriented partnerships in the United Kingdom and seeks to contrast public and private partnerships both in health and in health care. In the United Kingdom it is suggested that health care is conceived by the population to equate to the National Health Service(NHS) with "add on" private health care for certain sectors of the community and within certain well defined clinical parameters. This paper can provide us with valuable information on the characteristics of UK health care systems, current health policies as well as issues relating to the public and private partnerships in health/ health care in the UK, thus offer important policy implications for the improvement of Korean health care system which lacks health-oriented coordinations and partnership between public and private sector very considerably.

• Genomics & Informatics
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• 제9권4호
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• pp.197-199
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• 2011

The biological interpretation of two-dimensional (2D) gel electrophoresis experiments is a key step toward understanding the functions of biological systems. We here present a web-based integrated database, called 2DSpotDB, for the management of proteome data derived from several pathogens. The 2DSpotDB was established as a part of the management of a pathogen proteome project at the Korea National Institute of Health. The goals of the 2DSpotDB implementation are to store and define important pathogen genes, retrieve information obtained by 2D polyacrylamide gel electrophoresis and mass spectrometry, and create an integrated system to provide pathogen proteome information for biological scientists. This database currently contains 14 gels and information on 387 protein spots, among which 329 proteins were identified and annotated.

• Journal of Preventive Medicine and Public Health
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• 제50권1호
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• pp.18-28
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• 2017

Objectives: Low birth weight (LBW) is a major public health concern, especially in developing countries, and is frequently related to child morbidity and mortality. This study aimed to identify key determinants that influence the prevalence of LBW in selected developing countries. Methods: Secondary data analysis was conducted using 10 recent Demography and Health Surveys from developing countries based on the availability of the required information for the years 2010 to 2013. Associations of demographic, socioeconomic, community-based, and individual factors of the mother with LBW in infants were evaluated using multivariate logistic regression analysis. Results: The overall prevalence of LBW in the study countries was 15.9% (range, 9.0 to 35.1%). The following factors were shown to have a significant association with the risk of having an LBW infant in developing countries: maternal age of 35 to 49 years (adjusted odds ratio [aOR], 1.7; 95% confidence interval [CI], 1.2 to 3.1; p<0.01), inadequate antenatal care (ANC) (aOR, 1.7; 95% CI, 1.1 to 2.8; p<0.01), illiteracy (aOR, 1.5; 95% CI, 1.1 to 2.7; p<0.001), delayed conception (aOR, 1.8; 95% CI, 1.4 to 2.5; p<0.001), low body mass index (aOR, 1.6; 95% CI, 1.2 to 2.1; p<0.001) and being in the poorest socioeconomic stratum (aOR, 1.4; 95% CI, 1.1 to 1.8; p<0.001). Conclusions: This study demonstrated that delayed conception, advanced maternal age, and inadequate ANC visits had independent effects on the prevalence of LBW. Strategies should be implemented based on these findings with the goal of developing policy options for improving the overall maternal health status in developing countries.

• Asian-Australasian Journal of Animal Sciences
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• 제28권9호
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• pp.1217-1225
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• 2015

Chicken is a major food source for humans, hence it is important to understand the mechanisms involved in nutrient absorption in chicken. In the gastrointestinal tract (GIT), the microbiota plays a central role in enhancing nutrient absorption and strengthening the immune system, thereby affecting both growth and health of chicken. There is little information on the diversity and functions of chicken GIT microbiota, its impact on the host, and the interactions between the microbiota and host. Here, we review the recent metagenomic strategies to analyze the chicken GIT microbiota composition and its functions related to improving metabolism and health. We summarize methodology of metagenomics in order to obtain bacterial taxonomy and functional inferences of the GIT microbiota and suggest a set of indicator genes for monitoring and manipulating the microbiota to promote host health in future.

• Earthquakes and Structures
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• 제8권3호
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• pp.541-553
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• 2015

Structural Health Monitoring (SHM) systems can provide valuable information regarding the safety of structures during and after ground motions which can be used by authorities to reduce post-earthquake hazards. Strain gages as a key element play an important role in the success of SHM systems. Reducing the number of required strain gages while keeping the efficiency of SHM system not only can reduce the cost of structural health monitoring but also avoids storage and process of uninformative data. In this study, a method based on performance based seismic design of structures is proposed for ideal placement of stain gages in structures. The robustness and efficiency of the proposed method is demonstrated through installation of strain gages on an Airport Traffic Control (ATC) Tower. The obtained results show that the number of required strain gages decrease significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.974-992
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• 2021

Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.

• 정보과학회지
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• 제35권7호
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• pp.9-25
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• 2017

In this paper, we surveyed state-of-the-art health and wellness platforms. The motivation of this paper is to review the state-of-the-art health and wellness platforms and their maturity with respect to adoption of latest enabling technologies. The is review is classified into four categories: healthcare systems, AI-assisted healthcare, wellness platforms, and open source health and wellness initiatives. From this comprehensive review, it can be stated that the contemporary healthcare systems are well-adopting wellness due to the concentration shift towards prevention. Thus, the gap between health and wellness is slowly yet carefully entering gray area. Where both the domains can freely invoke each other's services, and supporting enabling technologies. Furthermore, the biomedical researchers and physicians are no longer carrying the myopic views of trusting their knowledge for diagnosis. AI-assisted technologies based on machine learning and big data are influencing today's prognosis with trust and confidence.

• 전자공학회논문지 IE
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• 제49권2호
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• pp.82-88
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• 2012

본 논문에서는 안드로이드 기반의 모바일 플랫폼을 이용한 통합형 유헬스케어 시스템 설계하여 개인의 건강관리 서비스를 위한 시스템을 제안하였다. 통합형 생체 계측 시스템은 심전도, 산소포화도, 혈압, 호흡, 체온 등 모듈을 통하여 생체 신호를 계측하고 신호처리된 생체 정보를 무선 통신모듈을 이용하여 안드로이드 기반의 모바일 플랫폼 게이트웨이로 전송한다. 전송된 생체 데이터는 모바일 시스템에서 건강상태를 감시하거나 유헬스케어 서버로 전송하도로 설계하였다. 생체신호 감시 시스템을 구현함으로서 측정되어진 생체 데이터를 모니터링하여 현재의 건강상태를 확인할 수 있었으며 보호자의 이동성을 보장할 수 있는 장점을 보였다. 이와 같은 시스템은 개인 건강관리 및 응급환자 감시 시스템을 위한 유헬스케어 시스템 발전에 도움이 되리라 본다.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.84-92
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• 2021

Care services are a significant asset in human life. Care in its overall nature focuses on human needs and covers several aspects such as health care, homes, personal care, and education. In fact, care deals with many dimensions: physical, psychological, and social interconnections. Very little information is available on estimating the cost of care services that provided to orphans and abandoned children. Prediction of the cost of the care system delivered by governmental or non-governmental organizations to support orphans and abandoned children is increasingly needed. The purpose of this study is to analyze the care cost for orphanage organizations in Saudi Arabia to forecast the cost as well as explore the most influence factor on the cost. By using business analytic process that applied statistical and machine learning techniques, we proposed a model includes simple linear regression, Naive Bayes classifier, and Random Forest algorithms. The finding of our predictive model shows that Naive Bayes has addressed the highest accuracy equals to 87% in predicting the total care cost. Our model offers predictive approach in the perspective of business analytics.