- 영문명
- Research Trend Analysis by using Text-Mining Techniques on the Convergence Studies of AI and Healthcare Technologies
- 발행기관
- 한국IT서비스학회
- 저자명
- 윤지은(Jee-Eun Yoon) 서창진(Chang-Jin Suh)
- 간행물 정보
- 『한국IT서비스학회지』한국IT서비스학회지 제18권 제2호, 123~141쪽, 전체 19쪽
- 주제분류
- 경제경영 > 경영학
- 파일형태
- 발행일자
- 2019.06.30

국문 초록
영문 초록
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.
목차
1. 서 론
2. 연구방법
3. 연구결과
4. 결 론
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