Journal of Information Technology Services (한국IT서비스학회지)

Korea Society of IT Services (한국IT서비스학회)
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Research Trend Analysis by using Text-Mining Techniques on the Convergence Studies of AI and Healthcare Technologies

텍스트 마이닝 기법을 활용한 인공지능과 헬스케어 융·복합 분야 연구동향 분석

  • 윤지은 (한양대학교 일반대학원 경영학과) ;
  • 서창진 (한양대학교 경영학부)
  • Received : 2019.02.07
  • Accepted : 2019.05.25
  • Published : 2019.06.30
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Abstract

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

Keywords

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Analysis Flowchart of Study

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Result of 2-Mode Network(Topic-Word)

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Changes in Number of Topic

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Changes of the Number of Article(Topic 1)

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Result of Word Cloud(Topic 1)

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Ego Network Analysis(Topic 1)

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Changes of the Number of Article(Topic 2)

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Result of Word Cloud(Topic 2)

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Ego Network Analysis(Topic 2)

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Changes of the Number of Article(Topic 3)

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Result of Word Cloud(Topic 3)

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Ego Network Analysis(Topic 3)

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Changes of the Number of Article(Topic 4)

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Result of Word Cloud(Topic 4)

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Ego Network Analysis(Topic 4)

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Changes of the Number of Article(Topic 5)

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Result of Word Cloud(Topic 5)

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Ego Network Analysis(Topic 5)

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Changes of the Number of Article(Topic 6)

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Result of Word Cloud(Topic 6)

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Ego Network Analysis(Topic 6)

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Changes of the Number of Article(Topic 7)

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Result of Word Cloud(Topic 7)

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Ego Network Analysis(Topic 7)

Customer Dictionary

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Result of Frequency Analysis

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Result of Topic Modeling

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