@article{ART002419494},
author={Tae-Gyeong Lee and Seong-Min Heo and Shin,Seung-Hyeok and yang ji yeon},
title={Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2018},
volume={23},
number={12},
pages={153-161},
doi={10.9708/jksci.2018.23.12.153}
TY - JOUR
AU - Tae-Gyeong Lee
AU - Seong-Min Heo
AU - Shin,Seung-Hyeok
AU - yang ji yeon
TI - Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques
JO - Journal of The Korea Society of Computer and Information
PY - 2018
VL - 23
IS - 12
PB - The Korean Society Of Computer And Information
SP - 153
EP - 161
SN - 1598-849X
AB - In this paper, we propose a text-centered approach to identify the research trend of thyroid cancer in Korea. We incorporate statistical analysis, text mining and machine learning techniques with our clinical insights to find connective associations between terminologies and to discover informative clusters of literatures. The incidence of thyroid cancer in Korea increased rapidly in the 2000s, which fueled the debate regarding overdiagnosis, but recently the number of patients undergoing surgery has decreased significantly due to conscious reform efforts from various circles. We analyzed the abstracts and keywords of related research papers from DBpia. It was found that most were case reports in the 1980s, and some papers in the 1990s discussed the early detection of thyroid cancer by mass screening. While many papers focused on different diagnostic techniques and the detection of small cancers in the 2000s, many emphasized more on the quality of life of patients in the 2010s.
There was an apparent change in the topics of thyroid cancer research over past decades. The results of this study would serve as a reference guide for current and future research directions.
KW - hierarchical clustering;social network;text mining;thyroid cancer;word cloud
DO - 10.9708/jksci.2018.23.12.153
ER -
Tae-Gyeong Lee, Seong-Min Heo, Shin,Seung-Hyeok and yang ji yeon. (2018). Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques. Journal of The Korea Society of Computer and Information, 23(12), 153-161.
Tae-Gyeong Lee, Seong-Min Heo, Shin,Seung-Hyeok and yang ji yeon. 2018, "Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques", Journal of The Korea Society of Computer and Information, vol.23, no.12 pp.153-161. Available from: doi:10.9708/jksci.2018.23.12.153
Tae-Gyeong Lee, Seong-Min Heo, Shin,Seung-Hyeok, yang ji yeon "Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques" Journal of The Korea Society of Computer and Information 23.12 pp.153-161 (2018) : 153.
Tae-Gyeong Lee, Seong-Min Heo, Shin,Seung-Hyeok, yang ji yeon. Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques. 2018; 23(12), 153-161. Available from: doi:10.9708/jksci.2018.23.12.153
Tae-Gyeong Lee, Seong-Min Heo, Shin,Seung-Hyeok and yang ji yeon. "Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques" Journal of The Korea Society of Computer and Information 23, no.12 (2018) : 153-161.doi: 10.9708/jksci.2018.23.12.153
Tae-Gyeong Lee; Seong-Min Heo; Shin,Seung-Hyeok; yang ji yeon. Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques. Journal of The Korea Society of Computer and Information, 23(12), 153-161. doi: 10.9708/jksci.2018.23.12.153
Tae-Gyeong Lee; Seong-Min Heo; Shin,Seung-Hyeok; yang ji yeon. Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques. Journal of The Korea Society of Computer and Information. 2018; 23(12) 153-161. doi: 10.9708/jksci.2018.23.12.153
Tae-Gyeong Lee, Seong-Min Heo, Shin,Seung-Hyeok, yang ji yeon. Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques. 2018; 23(12), 153-161. Available from: doi:10.9708/jksci.2018.23.12.153
Tae-Gyeong Lee, Seong-Min Heo, Shin,Seung-Hyeok and yang ji yeon. "Trend Analysis of Thyroid Cancer Research in Korea with Text Mining Techniques" Journal of The Korea Society of Computer and Information 23, no.12 (2018) : 153-161.doi: 10.9708/jksci.2018.23.12.153
