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Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data
KyungSang Lee,Hyewon Lee,Woojae Myung,GilYoung Song,Kihwang Lee,Ho Kim,Bernard J. Carroll,DohKwan Kim 대한신경정신의학회 2018 PSYCHIATRY INVESTIGATION Vol.15 No.4
Objective-Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. Methods-The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Results-Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. Conclusion-These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events.
Identification of Keywords From Twitter and Web Blog Posts to Detect Influenza Epidemics in Korea
Woo, Hyekyung,Sung Cho, Hyeon,Shim, Eunyoung,Lee, Jong Koo,Lee, Kihwang,Song, Gilyoung,Cho, Youngtae Cambridge University Press 2018 Disaster medicine and public health preparedness Vol.12 No.3
<B>Abstract</B><B>Objective</B><P>Social media data are a highly contextual health information source. The objective of this study was to identify Korean keywords for detecting influenza epidemics from social media data.</P><B>Methods</B><P>We included data from Twitter and online blog posts to obtain a sufficient number of candidate indicators and to represent a larger proportion of the Korean population. We performed the following steps: initial keyword selection; generation of a keyword time series using a preprocessing approach; optimal feature selection; model building and validation using least absolute shrinkage and selection operator, support vector machine (SVM), and random forest regression (RFR).</P><B>Results</B><P>A total of 15 keywords optimally detected the influenza epidemic, evenly distributed across Twitter and blog data sources. Model estimates generated using our SVM model were highly correlated with recent influenza incidence data.</P><B>Conclusions</B><P>The basic principles underpinning our approach could be applied to other countries, languages, infectious diseases, and social media sources. Social media monitoring using our approach may support and extend the capacity of traditional surveillance systems for detecting emerging influenza. (<I>Disaster Med Public Health Preparedness</I>. 2018; 12: 352-359)</P>
Eui-Seon Lee,Tae-Young Kim,Yam Prasad Aryal,Kihyun Kim,Seongsoo Byun,Dongju Song,Yejin Shin,Dany Lee,Jooheon Lee,Gilyoung Jung,Seunghoon Chi,Yoolim Choi,Youngkyun Lee,Chang-Hyeon An,Jae-Young Kim 대한구강생물학회 2021 International Journal of Oral Biology Vol.46 No.2
This study summarizes the recent cutting-edge approaches for dentin regeneration that still do not offer adequate solutions. Tertiary dentin is formed when odontoblasts are directly affected by various stimuli. Recent preclinical studies have reported that stimulation of the Wnt/β-catenin signaling pathway could facilitate the formation of reparative dentin and thereby aid in the structural and functional development of the tertiary dentin. A range of signaling pathways, including the Wnt/β-catenin pathway, is activated when dental tissues are damaged and the pulp is exposed. The application of small molecules for dentin regeneration has been suggested as a drug repositioning approach. This study reviews the role of Wnt signaling in tooth formation, particularly dentin formation and dentin regeneration. In addition, the application of the drug repositioning strategy to facilitate the development of new drugs for dentin regeneration has been discussed in this study.