• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.318-321
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• 2022

최근 의료데이터 표준화에 대한 중요성이 보건의료 빅데이터 구축과 맞물려 보건의료데이터 표준화와 마이데이터 생태계 조성을 추진하고 있다. 그리고 개인들의 휴대용 기기 이용증가와 모바일 환경으로 전반적인 디지털헬스의 패러다임 변화에 따라 HL7 FHIR의 사용이 점차 확대될 것으로 예측된다. 본 논문에서는 의료정보 표준인 HL7 FHIR와 의료영상 표준인 DICOM으로 환자 정보를 전달하기 위한 다중 의료 정보 중재 플랫폼에 대해서 기술한다. 이를 구현하기 위해 HL7 FHIR의 Patient, Observation, DiagnosticReport, Bundle 리소스를 활용하여 환자 정보와 임상 리포트 정보를 전달하여 StudyList에서 보여줄 수 있도록 구현하였다. 현재 구현된 내용은 FHIR 기반의 임상데이터로 의료영상을 포함한 표준화된 정보로 제공하여 마이데이터 실증 플랫폼으로 활용될 것으로 기대된다.

• The Journal of Bigdata
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• v.4 no.2
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• pp.195-205
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• 2019

Linked Open Data (LOD) is rated as the best of any kind of data disclosure, and allows you to search related data by linking them in a standard format across the Internet. There is an increasing number of cases in which relevant data are constructed in the LOD form in the global environment, but in the domestic healthcare sector, the disclosure of data in the form of LOD is still at the beginning stage. In this paper, we introduce a case of LOD platform construction that provides services by linking domestic and international related data by LOD method, based on the data of Korean medical research paper data and health care big data linkage platform. Linking all data from each DB into an LOD requires a lot of time and effort, and is basically an infrastructure task that government or public institutions should be in charge of rather than the private sector. In this study, ten domestic and foreign LOD sites were linked with only a portion of each DB, enabling users to link data from various domestic and foreign organizations in a convenient manner.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.38-39
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• 2019

본 논문은 R-CDM 의료영상정보를 기반으로 ELK Stack 기술을 적용하여 획득한 데이터의 분석 결과를 시각화하기 위한 시스템에 대해 기술한다. 제안한 시스템은 의료 빅데이터의 검색, 수집 그리고 분석 결과를 모니터링 할 수 있으며, 특히 대량의 데이터의 변화와 데이터간의 차이를 확인할 수 있다. 본 연구에서 제안한 시스템은 수집된 의료영상 빅데이터에 대해 적용하여 현황과 처리결과 그리고 실시간 분석결과에 대한 모니터링을 통해 관리의 효율성을 높여 실시간 검색 및 분석 서비스 분야에 기여할 것으로 기대된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.513-516
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• 2013

In this paper, we present an information collecting system in medical information management domain. Our proposed system performs a systemized process, consisting of collection, transmission, and management, to develop intelligent medical information system and medical big data processing system. Our information collecting system consists of low-power biomedical sensors, biomedical information collecting devices, and storage systems. Currently, almost biomedical information of patients is collected manually by employees like nurses and medical doctors. Therefore, collected biometric data can be error-pronoun data. Since there is a lack to make big data of medical information, it is difficult to enhance the quality of medical services and researches. Accordingly, through our proposed system, we can overcome the problems like error-pronoun biometric data. In addition, we can extremely extend the area of collectable biometric data. Furthermore, using this system, we are able to make a real-time biomedical analysis system, like a real-time patient diagnosis system, and establish a strategy to against future medical markets changing rapidly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.551-554
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• 2017

The largest industry in the world is the medical industry, and due to aging and growing demand for well-being, it is necessary to review the competition strategy of the healthcare industry. We will secure competitiveness among medical institutions through the rapid dissemination of ICT convergence, study the intelligence level of digital health care by increasing the capacity of intelligent medical care by combining big data of medical data and artificial intelligence, And to find a countermeasure for constructing a medical optimization model.

• Journal of Convergence Society for SMB
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• v.5 no.1
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• pp.1-6
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• 2015

Recently the disease by eating of the modern prevention, management, and trends in the u-healthcare service that provides healthcare services including health promotion is changing rapidly. However, u-healthcare service is a healthcare information that provides users of the disease can not be analyzed even if the service is stored or not stored in the management server status is giving the inconvenience caused to users of the health services. In this paper, we propose a management method of health care services and a big data formation information that provides users of the disease to facilitate the users of health care services through the use magazine big data information regardless of time and place. The proposed method has the user's bio-information and the measured health information and transmits data through a wired or wireless communication to the medical institution and the user's health information data formation by the big user of the analysis of the health information and the disease of the user feedback to the user.

• Management & Information Systems Review
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• v.39 no.3
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• pp.17-35
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• 2020

The purpose of this study is to develop business models for current situational scenarios reflecting customer needs emphasize the need for implementing a logistics cooperation system by analyzing big data to strengthen SCM competitiveness capacities. For healthcare SCM competitiveness needed for the logistics cooperation usage intent, they were divided into product quality, price leadership, hand-over speed, and process flexibility for examination. The wordcloud results that analyzed major considerations to realize work efficiency between medical institutes, words like unexpected situations, information sharing, delivery, real-time, delivery, convenience, etc. were mentioned frequently. It can be analyzed as expressing the need to construct a system that can immediately respond to emergency situations on the weekends. Furthermore, in addition to pursuing communication and convenience, the importance of real-time information sharing that can share to the efficiency of inventory management were evident. Accordingly, it is judged that it is necessary to aim for a business model that can enhance visibility of the logistics pipeline in real-time using big data analysis on site. By analyzing the effects of the adaptability of a supply chain network for healthcare SCM competitiveness, it was revealed that obtaining competitive capacities is possible through the implementation of logistics cooperation. Stronger partnerships such as logistics cooperation will lead to SCM competitive capacities. It will be necessary to strengthen SCM competitiveness by searching for a strategic approach among companies in a direction that can promote mutual partnerships among companies using the joint logistics system of medical institutes. In particular, it will be necessary to search for ways to utilize HCSM through big data analysis according to the construction of a logistics cooperation system.

• Industry Promotion Research
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• v.7 no.3
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• pp.17-26
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• 2022

As the well-being mindset to keep our minds and bodies free and healthy more than anything else in the society we live in is spreading, the meaning of health care has become a key part of the 4th industrial revolution such as big data, IoT, AI, and block chain. The advancement of the advanced medical information service industry is being promoted by utilizing convergence technology. In digital healthcare, the development of intelligent information technology such as artificial intelligence, big data, and cloud is being promoted as a digital transformation of the traditional medical and healthcare industry. In addition, due to rapid development in the convergence of science and technology environment, various issues such as health, medical care, welfare, etc., have been gradually expanded due to social change. Therefore, in this study, first, the general meaning and current status of digital health care medical information is examined, and then, developmental tasks to activate digital health care medical information are analyzed and reviewed. The purpose of this article is to improve usability to fully pursue our human freedom.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.835-841
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• 2018

In this study, we analyzed public health data analysis using the hadoop-based spack in the cloud environment using the data of the Community Health Survey from 2012 to 2014, and the factors affecting the quality of life and quality of life. In the proposed paper, we constructed a cloud manager for parallel processing support using Hadoop - based Spack for open medical big data analysis. And we analyzed the factors affecting the "quality of life" of the individual among open medical big data quickly without restriction of hardware. The effects of public health data on health - related quality of life were classified into personal characteristics and community characteristics. And multiple-level regression analysis (ANOVA, t-test). As a result of the experiment, the factors affecting the quality of life were 73.8 points for men and 70.0 points for women, indicating that men had higher health - related quality of life than women.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1460-1465
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• 2016

Lots of costs threaten the sustainability of the national health-guarantee system. Despite research by the national center for disease control and prevention on health care dynamics with its auditing systems, there are still restrictions of time limitation, sample limitation, and, target diseases limitation. Against this backdrop, using huge volume of total data, many technologies could be fully adopted to the preliminary forecasting and its target-disease expanding of health. With structured data from the national health insurance and unstructured data from the social network service, we attempted to design a model to predict disease. The model can enhance national health and maximize social benefit by providing a health warning service. Also, the model can reduce the advent increase of national health cost and predict timely disease occurrence based on Big Data analysis. We researched related medical prediction cases and performed an experiment with a pilot project so as to verify the proposed model.