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Classification analysis using hidden Markov model
Yeji Cheon,Hayoung Choi,Yongku Kim 한국데이터정보과학회 2021 한국데이터정보과학회지 Vol.32 No.5
A hidden Markov model (HMM) provides useful representations of dependent heterogeneous phenomena. So it becomes a popular method for modelling stochastic processes and time-dependent sequences, and is primarily applied in many different fields such as language, handwriting recognition, and molecular biology. Especially, in the sequence classification case, classification among known hidden Markov models is known to be accomplished with a classifier that minimizes the probability of error. In this paper, we first generate variables for the hidden state using the hidden markov model and then analyze the state using various classification methods. It differs from the existing analysis method by using the state variable and the mixture distribution based on the state rather than using the observed value directly in the analysis. In addition, it can be used to identify the relevance in the underlying process. As as illustration, we used the annual production of Matsutake mushroom data observed in five regions from 1997 to 2016.
보건복지통계 현황과 발전 과제: 보건복지부 소관 국가승인통계를 중심으로
신정우 ( Shin Jeongwoo ),천미경 ( Cheon Mikyung ),전예지 ( Jeon Yeji ),진재현 ( Jin Jaehyun ) 한국보건사회연구원 2022 보건복지포럼 Vol.313 No.-
The Ministry of Health and Welfare (MOHW) establishes a national statistical development plan every five years. The new 5 year plan is to be implemented for the years 2023~2027. In order for the new plan to present the right direction, considerable analysis must be preceded. According to the analysis of national approval statistics, the MOHW lacks the designated statistics that are the basis of national policy design. And the statistical verification of the national indicators that monitor the current state of national policy is partially insufficient, so this should be improved. In addition, efforts should be made to strengthen the work network between related agencies and to produce and provide accurate and reliable statistical information in a position to integrate and coordinate statistics in the health and welfare sector.
Jae-Hyung Roh,Hyun Jun Cho,Jae-Hwan Lee,Yongku Kim,Yeongwoo Park,Jae-Hyeong Park,Hee-Soon Park,Minsu Kim,Hyang Gon Jin,Yeji Cheon,In-Whan Seong 대한심장학회 2020 Korean Circulation Journal Vol.50 No.4
Background and Objectives: There is insufficient evidence regarding the optimal treatment for asymptomatic carotid stenosis. Methods: Bayesian cross-design and network meta-analyses were performed to compare the safety and efficacy among carotid artery stenting (CAS), carotid endarterectomy (CEA), and medical treatment (MT). We identified 18 studies (4 randomized controlled trials [RCTs] and 14 nonrandomized, comparative studies [NRCSs]) comparing CAS with CEA, and 4 RCTs comparing CEA with MT from MEDLINE, Cochrane Library, and Embase databases. Results: The risk for periprocedural stroke tended to increase in CAS, compared to CEA (odds ratio [OR], 1.86; 95% credible interval [CrI], 0.62–4.54). However, estimates for periprocedural myocardial infarction (MI) were quite heterogeneous in RCTs and NRCSs. Despite a trend of decreased risk with CAS in RCTs (OR, 0.70; 95% CrI, 0.27–1.24), the risk was similar in NRCSs (OR, 1.02; 95% CrI, 0.87–1.18). In indirect comparisons of MT and CAS, MT showed a tendency to have a higher risk for the composite of periprocedural death, stroke, MI, or nonperiprocedural ipsilateral stroke (OR, 1.30; 95% CrI, 0.74–2.73). Analyses of study characteristics showed that CEA-versus-MT studies took place about 10-year earlier than CEA-versus-CAS studies. Conclusions: A similar risk for periprocedural MI between CEA and CAS in NRCSs suggested that concerns about periprocedural MI accompanied by CEA might not matter in real-world practice when preoperative evaluation and management are working. Maybe the benefits of CAS over MT have been overestimated considering advances in medical therapy within10-year gap between CEA-versus-MT and CEA-versus-CAS studies.