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http://dx.doi.org/10.9716/KITS.2019.18.2.123

Research Trend Analysis by using Text-Mining Techniques on the Convergence Studies of AI and Healthcare Technologies  

Yoon, Jee-Eun (한양대학교 일반대학원 경영학과)
Suh, Chang-Jin (한양대학교 경영학부)
Publication Information
Journal of Information Technology Services / v.18, no.2, 2019 , pp. 123-141 More about this Journal
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
Artificial Intelligence(AI); Healthcare; Text Mining; Topic Modeling; Ego Network Analysis; Word Cloud;
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Times Cited By KSCI : 2  (Citation Analysis)
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