• Title/Summary/Keyword: 공개의료 빅데이터

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An Analysis of Factors Affecting Quality of Life through the Analysis of Public Health Big Data (클라우드 기반의 공개의료 빅데이터 분석을 통한 삶의 질에 영향을 미치는 요인분석)

  • Kim, Min-kyoung;Cho, Young-bok
    • 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.

System Implementation of Utilization of Health and Medical Treatment Big Data (공공의료 빅데이터 활용을 위한 시스템 구축 방안에 관한 연구)

  • Choi, Eunjoo;Kim, Gi-Yoon;Moon, Yoo-Jin
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2017.07a
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    • pp.397-398
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    • 2017
  • 정보 공유를 통해 국민들은 의료 기관 및 치료방법 등을 합리적으로 선택하려고 노력하고 있다. 의료 기관의 컴퓨터와 연결 기계의 사용으로 의료 관련 데이터는 규모가 급격히 늘어났다. 이에 따라 정부 3.0에 맞춰 공개되는 의료 데이터가 확대됨에 따라 의료 빅데이터를 통해 여러 정보들을 만들어내 의료 분야에 도움이 될 것이라는 기대가 커져가고 있다. 이 연구에서는 의료 빅데이터를 어떻게 활용하여 의료 기관, 국민, 정부, 보험사 등 여러 기관에게 제공할 수 있는 지에 대해 설명한다. 현재 빅 데이터를 사용해 연령 별 잘 걸리는 질병이나 질병 별 성비를 나타내는 것 등 단순 사실을 알아내는 정도가 아니라 실질적으로 다양한 목적으로 사용될 수 있는 정보를 만들어낼 수 있는 시스템을 구축하였다는 점에서 이 연구는 강점을 갖는다.

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Data Linkage Method Using LOD in the Healthcare Big Data Platform (보건의료 빅데이터 플랫폼에서 LOD를 활용한 데이터 연계 방안)

  • Lee, Kyung-Hee;Kim, Kinam;Cho, Wan-Sup
    • 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.

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Usefulness of RHadoop in Case of Healthcare Big Data Analysis (RHadoop을 이용한 보건의료 빅데이터 분석의 유효성)

  • Ryu, Wooseok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.115-117
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    • 2017
  • R has become a popular analytics platform as it provides powerful analytic functions as well as visualizations. However, it has a weakness in which scalability is limited. As an alternative, the RHadoop package facilitates distributed processing of R programs under the Hadoop platform. This paper investigates usefulness of the RHadoop package when analyzing healthcare big data that is widely open in the internet space. To do this, this paper has compared analytic performances of R and RHadoop using the medical treatment records of year 2015 provided by National Health Insurance Service. The result shows that RHadoop effectively enhances processing performance of healthcare big data compared with R.

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Linked Open Data Construction for Korean Healthcare News (국내 언론사 보건의료 뉴스의 Linked Open Data 구축)

  • Jang, Jong-Seon;Cho, Wan-Sup;Lee, Kyung-hee
    • The Journal of Bigdata
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    • v.1 no.2
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    • pp.79-89
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    • 2016
  • News organizations are looking for a way that can be reused accumulated intellectual property in order to find a new insights. BBC is a worldwide media that continually enhances the value of the news articles by using Linked Data model. Thus, utilizing the Linked Data model, by reusing the stored articles, can significantly improve the value of news articles. In this paper, we conducted a study of Linked Data construction for the healthcare news from a newspaper company. The object names associated with medical description or connected to other published information have been constructed into Linked Open Data service. The results of the study are to systematically organize the news data that were accumulated rashly, and to provide the opportunity to find new insights that could not be found before by connecting to other published information. It may be able to contribute to reused news data. Finally, using SPARQL query language can contribute to interactively searched news data.

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Performance Evaluation of Medical Big Data Analysis based on RHadoop (RHadoop 기반 보건의료 빅데이터 분석의 성능 평가)

  • Ryu, Woo-Seok
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.1
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    • pp.207-212
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    • 2018
  • As a data analysis tool which is becoming popular in the Big Data era, R is rapidly expanding its user range by providing powerful statistical analysis and data visualization functions. Major advantage of R is its functional scalability based on open source, but its scale scalability is limited, resulting in performance degrades in large data processing. RHadoop, one of the extension packages to complement it, can improve data analysis performance as it supports Hadoop platform-based distributed processing of programs written in R. In this paper, we evaluate the validity of RHadoop by evaluating the performance improvement of RHadoop in real medical big data analysis. Performance evaluation of the analysis of the medical history information, which is provided by National Health Insurance Service, using R and RHadoop shows that RHadoop cluster composed of 8 data nodes can improve performance up to 8 times compared with R.

Implementation of Disease Search System Based on Public Data using Open Source (오픈 소스를 활용한 공공 데이터 기반의 질병 검색 시스템 구현)

  • Park, Sun-ho;Kim, Young-kil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.11
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    • pp.1337-1342
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    • 2019
  • Medical institutions face the challenge of securing competitiveness among medical institutions due to the rapid spread of ICT convergence, and managing data that is growing at an enormous rate due to the emergence of big data and the emergence of the Internet of Things. The big data paradigm of the medical community is not just about large data or tools and processes for processing and analyzing it, but also means a computerized shift in the way people live, think and study. As the medical data is recently released, the demand for the use of medical data is increasing. Therefore, the research on disease detection system based on public data using open source that can help rational and efficient decision making was conducted. As a result of the experiment, unlike a simple disease inquiry or a symptom inquiry about a single disease provided by a public institution, related diseases are searched by a symptom or a cause.

Analysis of Factors for Korean Women's Cancer Screening through Hadoop-Based Public Medical Information Big Data Analysis (Hadoop기반의 공개의료정보 빅 데이터 분석을 통한 한국여성암 검진 요인분석 서비스)

  • Park, Min-hee;Cho, Young-bok;Kim, So Young;Park, Jong-bae;Park, Jong-hyock
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.10
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    • pp.1277-1286
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    • 2018
  • In this paper, we provide flexible scalability of computing resources in cloud environment and Apache Hadoop based cloud environment for analysis of public medical information big data. In fact, it includes the ability to quickly and flexibly extend storage, memory, and other resources in a situation where log data accumulates or grows over time. In addition, when real-time analysis of accumulated unstructured log data is required, the system adopts Hadoop-based analysis module to overcome the processing limit of existing analysis tools. Therefore, it provides a function to perform parallel distributed processing of a large amount of log data quickly and reliably. Perform frequency analysis and chi-square test for big data analysis. In addition, multivariate logistic regression analysis of significance level 0.05 and multivariate logistic regression analysis of meaningful variables (p<0.05) were performed. Multivariate logistic regression analysis was performed for each model 3.

Ethical Issues in the Forth Industrial Revolution and the Enhancement of Bioethics Education in Korean Universities (4차 산업혁명 시대의 윤리적 이슈와 대학의 생명윤리교육 방향 제고)

  • KIM, Sookyung;LEE, Kyunghwa;KIM, Sanghee
    • Korean Journal of Medical Ethics
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    • v.21 no.4
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    • pp.330-343
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    • 2018
  • This article explores some of the ethical issues associated with the fourth industrial revolution and suggests new directions for bioethics education in Korean universities. Some countries have recently developed guidelines and regulations based on the legal and ethical considerations of the benefits and social risks of new technologies associated with the fourth industrial revolution. Foreign universities have also created courses (both classroom and online) that deal with these issues and help to ensure that these new technologies are developed in an ethically appropriate fashion. In South Korea too there have been attempts to enhance bioethics education to meet the changing demands of society. However, bioethics education in Korea remains focused on traditional bioethical topics and largely neglects the ethical issues related to emerging technologies. Furthermore, Korean universities offer no online courses in bioethics and the classroom courses that do exist are generally treated as electives. In order to improve bioethics education in Korean universities, we suggest that (a) new course should be developed for interprofessional education; (b) courses in bioethics should be treated as required subjects gradually; (c) online courses should be prepared, and (d) universities should continually revise course contents in response to the development of new technologies.