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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 (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)
  • Received : 2018.05.03
  • Accepted : 2018.08.20
  • Published : 2018.10.31

Abstract

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.

Acknowledgement

Supported by : National Research Foundation of Korea(NRF)

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