The Journal of Bigdata (한국빅데이터학회지)

Korea Bigdata Society (한국빅데이터학회)
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Statistical Data Extraction and Validation from Graph for Data Integration and Meta-analysis

데이터통합과 메타분석을 위한 그래프 통계량 추출과 검증

  • 심성률 (차의과학대학교 의학전문대학원 정보의학교실) ;
  • 임요환 (차의과학대학교 의학전문대학원 정보의학연구소) ;
  • 홍명희 (차의과학대학교 의학전문대학원 정보의학교실) ;
  • 송규선 (차의과학대학교 의학전문대학원 정보의학교실) ;
  • 한현욱 (차의과학대학교 의학전문대학원 정보의학교실)
  • Received : 2021.11.26
  • Accepted : 2021.12.13
  • Published : 2021.12.31
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Abstract

The objective of this study was to describe specific approaches for data extraction from graph when statistical information is not directly reported in some articles, enabling data intergration and meta-analysis for quantitative data synthesis. Particularly, meta-analysis is an important analysis tool that allows the right decision making for evidence-based medicine by systematically and objectively selects target literature, quantifies the results of individual studies, and provides the overall effect size. For data integration and meta-analysis, we investigated the strength points about the introduction and application of Adobe Acrobet Reader and Python-based Jupiter Lab software, a computer tool that extracts accurate statistical figures from graphs. We used as an example data that was statistically verified throught an previous studies and the original data could be obtained from ClinicalTrials.gov. As a result of meta-analysis of the original data and the extraction values of each computer software, there was no statistically significant difference between the extraction methods. In addition, the intra-rater reliability of between researchers was confirmed and the consistency was high. Therefore, In terms of maintaining the integrity of statistical information, measurement using a computational tool is recommended rather than the classically used methods.

본 연구의 목적은 개별연구들이 정확한 통계량을 제시하지 않고 그래프로만 나타내었을 경우 그래프로부터 통계량을 추출해내는 구체적인 방법을 기술한 것으로서 데이터통합과 정량적합성을 위한 메타분석을 가능하게 한다. 특히 메타분석(meta-analysis)은 체계적·객관적으로 대상문헌을 선택한 후 개별 연구들의 결과를 계량화하여 이를 통합된 효과크기(effect size)로 제시함으로써 근거중심의학(evidence based medicine)를 위한 올바른 의사결정을 할 수 있게 하는 중요한 분석도구이다. 데이터통합과 메타분석을 위해서 그래프로부터 정확한 통계수치를 추출하는 전산도구인 Adobe Acrobat Reader 와 Python기반의 JupyterLab 소프트웨어의 소개와 적용에 대한 주요사항을 알아보았다. 사용된 예제자료는 선행연구를 통해서 통계결과가 검증되어졌고 ClinicalTrials.gov에서 원자료 확보가 가능한 것을 사용하였다. 원자료와 각 전산도구들의 측정값을 각각 메타분석한 결과 통계적으로 유의한 차이는 없었다. 또한 연구자들간의 측정 신뢰도를 확인하였으며 높은 일치도를 나타내었다. 만약 그래프로부터 통게수치를 추출해야만 할 경우 연구의 완결성 유지를 위해서 전통적 사용 방법들보다는 전산 도구를 이용한 측정이 권고된다.

Keywords

Acknowledgement

본 연구는 교육부 지원의 한국연구재단 기초과학연구 (과제번호: NRF-2019M3C7A1032262), 산업통상자원부 지원의 바이오산업기술개발 프로그램 (과제번호: 20015086), 그리고 과학기술정보통신부 산하 정보통신산업진흥원 지원의 정보통신촉진기금 연구개발비로 수행되었으며 이에 감사드립니다.

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