한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제22권10호
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  • Pages.1277-1286
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  • 2018
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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Hadoop기반의 공개의료정보 빅 데이터 분석을 통한 한국여성암 검진 요인분석 서비스

Analysis of Factors for Korean Women's Cancer Screening through Hadoop-Based Public Medical Information Big Data Analysis

  • Park, Min-hee (Department of Convergence in Health and Biomedicine Program in Health Policy Graduate, School, Chungbuk National University) ;
  • Cho, Young-bok (Department of Computer & Information Security, Daejeon University) ;
  • Kim, So Young (Department of Pubic Health and Preventive Medicine, Chungbuk National University Hospital) ;
  • Park, Jong-bae (Department of Radiology, Chungbok Health & Science University) ;
  • Park, Jong-hyock (Department of Convergence in Health and Biomedicine Program in Health Policy Graduate, School, Chungbuk National University)
  • 투고 : 2018.05.03
  • 심사 : 2018.08.20
  • 발행 : 2018.10.31
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초록

본 논문에서는 공개의료정보 빅데이터 분석을 위해 클라우드 환경에서 아파치 하둡 기반의 클라우드 환경을 도입하여 컴퓨팅 자원의 유연한 확장성을 제공하고 실제로, 로그데이터가 장기간 축적되거나 급격하게 증가하는 상황에서 스토리지, 메모리 등의 자원을 신속성 있고 유연하게 확장을 할 수 있는 기능을 포함했다. 또한, 축적된 비정형 로그데이터의 실시간 분석이 요구되어질 때 기존의 분석도구의 처리한계를 극복하기 위해 본 시스템은 하둡 (Hadoop) 기반의 분석모듈을 도입함으로써 대용량의 로그데이터를 빠르고 신뢰성 있게 병렬 분산 처리할 수 있는 기능을 제공한다. 빅데이터 분석을 위해 빈도분석과 카이제곱검정을 수행하고 유의 수준 0.05를 기준으로 단변량 로지스틱 회귀분석과 모델별 의미 있는 변수들의 다변량 로지스틱 회귀분석을 시행 하였다. (p<0.05) 의미 있는 변수들을 모델별로 나누어 다변량 로지스틱 회귀 분석한 결과 Model 3으로 갈수록 적합도가 높아졌다.

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.

키워드

과제정보

연구 과제 주관 기관 : National Research Foundation of Korea(NRF)

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피인용 문헌

  1. 빅데이터 기반 만성질환자의 삶의 질에 미치는 영향분석 vol.23, pp.11, 2018, https://doi.org/10.6109/jkiice.2019.23.11.1351