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Detecting Knowledge structures in Artificial Intelligence and Medical Healthcare with text mining

첫 페이지 보기
  • 발행기관
    한국경영정보학회 바로가기
  • 간행물
    Asia Pacific Journal of Information Systems KCI 등재 SCOPUS 바로가기
  • 통권
    제29권 제4호 (2019.12)바로가기
  • 페이지
    pp.817-837
  • 저자
    Hyun-A Lim, Pham Duong Thuy Vy, Jaewon Choi
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A367259

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원문정보

초록

영어
The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Review
2.1. Smart Medical Healthcare
2.2. Information of Smart Medical Healthcare
2.3. Information Security for Smart Medicial Healthcare
Ⅲ. Research Methodology
3.1. Data Collection
3.2. Topic Modeling
3.3. Claume Newman Moore (CNM) Algorithm
Ⅳ. Data analysis and results
4.1. The trend of Smart Medical Healthcare Research
4.2. Smart Medicine Information Research Trends
4.3. The Research Trend of Security for Smart Medical Healthcare
Ⅴ. Discussion and Implications
5.1. Discussion of Findings
5.2. Limitations and Future Research Directions
5.3. Implications for Research and Practice
Ⅵ. Conclusion
Acknowledgements

키워드

Smart Medicine Medical Information Healthcare Topic Modeling Research Trend Analysis

저자

  • Hyun-A Lim [ M.S. Student Department of Business Administration, Global Business School, Soonchunhyang University, Korea ]
  • Pham Duong Thuy Vy [ M.S. Student Department of Business Administration, Global Business School, Soonchunhyang University, Korea ]
  • Jaewon Choi [ Assistant Professor, Department of Business Administration, Global Business School, Soonchunhyang University, Korea ] Corresponding author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국경영정보학회 [The Korea Society of Management information Systems]
  • 설립연도
    1989
  • 분야
    사회과학>경영학
  • 소개
    이 학회는 경영정보학의 연구 및 교류를 촉진하고 학문의 발전과 응용에 공헌함을 목적으로 합니다.

간행물

  • 간행물명
    Asia Pacific Journal of Information Systems
  • 간기
    계간
  • pISSN
    2288-5404
  • eISSN
    2288-6818
  • 수록기간
    1990~2026
  • 등재여부
    KCI 등재,SCOPUS
  • 십진분류
    KDC 325 DDC 658

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