• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.663-669
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• 2014

Background: With recent progress in health science administration, a huge amount of data has been collected from thousands of subjects. Statistical and computational techniques are very necessary to understand such data and to make valid scientific conclusions. The purpose of this paper was to develop a statistical probability model and to predict future survival times for male breast cancer patients who were diagnosed in the USA during 1973-2009. Materials and Methods: A random sample of 500 male patients was selected from the Surveillance Epidemiology and End Results (SEER) database. The survival times for the male patients were used to derive the statistical probability model. To measure the goodness of fit tests, the model building criterions: Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were employed. A novel Bayesian method was used to derive the posterior density function for the parameters and the predictive inference for future survival times from the exponentiated Weibull model, assuming that the observed breast cancer survival data follow such type of model. The Markov chain Monte Carlo method was used to determine the inference for the parameters. Results: The summary results of certain demographic and socio-economic variables are reported. It was found that the exponentiated Weibull model fits the male survival data. Statistical inferences of the posterior parameters are presented. Mean predictive survival times, 95% predictive intervals, predictive skewness and kurtosis were obtained. Conclusions: The findings will hopefully be useful in treatment planning, healthcare resource allocation, and may motivate future research on breast cancer related survival issues.

• Korean Journal of Acupuncture
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• v.37 no.3
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• pp.131-144
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• 2020

Objectives : The aim of this study is to analyze the details of acupuncture treatment methods and the reporting quality of acupuncture on Carpal Tunnel Syndrome (CTS). Methods : Search was conducted in Pubmed, EMBASE, and Cochrane Library for acupuncture studies on CTS. The reporting quality of acupuncture treatment was assessed using the following guidelines: Standards for Reporting Interventions in Clinical Trials of Acupuncture (STRICTA) for analyzing the method of acupuncture treatment, Consolidated Standards of Reporting Trials (CONSORT) for analyzing study design and study process, and Risk of Bias (ROB) for analyzing bias. The number of reported items was calculated and evaluated as a proportion. The reported proportion of each study was classified into three grades: Grade A (% score ≥75), Grade B (50≤ % score <75), and Grade C (% score <50). Results : A total of 9 Randomized Controlled Trials (RCTs) were included in this study. All trials reported 12 items (66.67%) on average in STRICTA guidelines. Five studies were conducted with manual acupuncture and 3 studies were conducted with electroacupuncture. PC7 (Daereung) was most frequently used to treat CTS. In STRICTA guideline evaluation, 3 studies were classified as Grade A, 5 studies were classified as Grade B, and 1 study was classified as Grade C. In the CONSORT statement assessment, all trials reported an average of 20.56 items. Of the 9 RCTs, 6 studies were classified as Grade B and 3 studies were classified as Grade C. In ROB assessment, most studies showed a low (63.49%) or unclear (26.98%) risk of bias. The selective reporting bias and the incomplete outcome data bias were found to have the lowest risk of bias, and the allocation concealment of selection bias was found to have the most unclear risk of bias. Conclusions : Recent acupuncture studies on CTS showed moderate reporting quality. However, more detailed reports on acupuncture are still needed to establish more solid evidence of acupuncture treatment.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

• Health Policy and Management
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• v.30 no.2
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• pp.185-191
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• 2020

Background: From January 2018, a policy was applied to differentially apply the co-payment for medical expenses of 15,000 won or more from 30% to 10%-30% for each medical fee. This policy lowers the burden on the medical use of the elderly, and it is necessary to analyze the effect of the policy by confirming changes in medical use and supply behavior after 2 years. Methods: The National Health Insurance Service's national medical use database was used. As for the analysis method, first, the medical use and medical supply behavior change over the age of 65 years were confirmed, and second, in order to check the net effect of the policy, the 66-year-old as the experimental group and the 63-year-old as the control group were selected as the control group. The propensity score matching was performed using the variables of age, living alone, income quartile, residence, disability, chronic disease, and co-morbid disease scores, and then it was analyzed using the difference in difference analysis method. Results: The share of the number of treatments under 15,000 won decreased from 37.0% in 2017 to 20.2% in 2018, while the share of the number of treatments under 15,001-20,000 won increased from 8.0% to 22.7%. It was confirmed that the reason for the increase in the cost of treatment per treatment was the result of the increase in the amount of physical therapy and examination. As a result of the policy effect, the burden of co-payment per person was reduced, and as a result, the number of hospital visits per person and the total medical cost per person increased. Conclusion: The self-pay rate differential policy reduced the burden of medical expenses for the elderly and confirmed the increase in medical use. However, the interpretation of the increase in medical use was not able to distinguish whether the unsatisfactory medical care was satisfied or the inducement demand. Efficient allocation of resources is a more important point in the future when the super-aged society is in front. It is necessary to prepare a plan to induce rational medical use within a range that does not impair the medical accessibility of the elderly.

• Resources Recycling
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• v.29 no.4
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• pp.45-50
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• 2020

Producer and distributor of electrical and electronic equipment may directly collect waste electrical and electronic equipment that falls under the class to which the equipment they distributed belongs, or may join KERC(Korea Electronic Recycling Cooperative) and have KERC fulfill the duty to collect on behalf. In this study, the system of calculating the financial contributions is reviewed, and then the defined problems and improvement plan are proposed. First, the standard operation and time should be set for collection and transportation costs, taking into account the operation by collection type. Second, since there is a difference in the screening method of the recycling center, the standard cost for the allocation factor should be set by reflecting the difference in these methods and the characteristics of the product line being processed. Third, it is necessary to secure a budget of sufficient size by determining the median or average value rather than the minimum value in the forecast model for visit collection. This study is suggesting in that it examines the problems of the allotted contributions paid by the mutual aid members to KERC and suggests ways to improve them.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.27 no.4
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• pp.1-15
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• 2014

Objective : This study was carried out to analyze the quality and quantity of Clinical Trials that have been published in the journal of korean medical ophthalmology, otolaryngology, dermatology(JKOOD). Methods : We analyzed 25 clinical trials that published in JKOOD from 1988 to 2014. We excluded case reports, protocol and retrospective studies and classified searched papers into three categories; Randomized Clinical Trials(RCT), Non Randomized Clinical Trials(NRCT), Before After Study(BAS) by using study Design Algorithm for Medical literature of Intervention(DMAI). All articles were analyzed according to diagnosis, statistics program and intervention period. The bias of RCTs were evaluated by Cochrane Risk of Bias(RoB). Result : 1. The number of searched journals is 25 papers; 13 RCT, 2 NRCT, 10 BAS 2. Distribution of clinical trial; 'Atopic dermatitis' ranked the highest(44%) in disease, 'External application' raked the highest(71%) in treatment method. 3. 'allocation sequence' and 'prevention of allocated intervent to patients and therapists' are graded 'Low' but 'incomplete outcome date' and 'selective outcome' are graded 'Uncertain'. Conclusions : It is necessary to study more RCT. It will be helpful to study systematic reviews and meta analysis in JKOOD.

• Korea Journal of Hospital Management
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• v.26 no.1
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• pp.71-82
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• 2021

Purpose: The purpose of this study is to estimate incomes and costs of the medical clinics by using secondary data. Methodology: The medical incomes and costs were estimated from 405 clinics operated by sole practitioner providing out-patient services among all clinics subject to the Medical Cost Survey on National Health Insurance Patients in 2017, excluding dental clinics and oriental medical clinics. The incomes and costs of the medical clinics were reflected with incomes and costs of health insurance benefits and were calculated by types of medical services (i.e., basic care, surgery, general treatment, functional test, specimen test and imaging test). The costs were classified as follows: labor costs, equipment costs, material costs and overhead costs. Secondary data was used to estimate the incomes and costs of the medical clinics. For allocation bases for costs for each type of the medical service, the ratio of revenue from health insurance benefits by types of medical services was applied. However, labor costs were calculated with the activity ratio by types of medical services and occupations, using clinical expert panel data. Finding: The percentage of health insurance income for all medical income was 73.1%. The health insurance cost per clinic was 401,864 thousand won. Labor cost accounted for the largest portion of the health insurance income was 191,229 thousand won (47.6%), followed by management cost was 170,018 thousand won (42.3%), materials cost was 35,434 thousand won (8.8%), and equipment costs was 5,183 thousand won (1.3%). Practical Implications: This study suggests a method of estimating incomes and costs of medical clinic services by using secondary data. It could efficiently provide incomes and costs to assess an appropriate level of the health insurance fee to the clinics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5B
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• pp.273-285
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• 2012

Current TMDL based on the 'Polluter Pays Principle' in Republic of Korea is individually operated by each local government for the designed allocated pollution load of unit watershed and unit district. However, unlike the motion of the air contaminants, the polluted contaminants in a river move from upstream to downstream, and a river can affect to districts more than two. In addition, a decision making on the construction of a sewage treatment facilities follows the concept of 'economy of scale'. These reasons support the collaboration among local governments in order to reduce the costs in improving water quality. This study suggested a method to reduce water quality management cost by redistributing reduction load considering cost-effectiveness for an entire watershed. The assessment on the suggested method is conducted in Youngsan river watershed. Without variation in total load, reduction load assigned for unit watershed and unit district is retributed in the region where pollutant source is concentrated, and then water quality and cost reduction improved from the redistribution of reduction load is analyzed. The results show that the cost saved by the suggested method is KRW 124 billion for scenario-1 and 172 billion for scenario-2 considering total cost of KRW 788 billion for the existing plan. We expect that the suggested method is a good example to reduce water quality management cost in local governments for TMDL.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8371-8376
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• 2014

Background: The use of statistical methods has become an imperative tool in breast cancer survival data analysis. The purpose of this study was to develop the best statistical probability model using the Bayesian method to predict future survival times for the black non-Hispanic female breast cancer patients diagnosed during 1973-2009 in the U.S. Materials and Methods: We used a stratified random sample of black non-Hispanic female breast cancer patient data from the Surveillance Epidemiology and End Results (SEER) database. Survival analysis was performed using Kaplan-Meier and Cox proportional regression methods. Four advanced types of statistical models, Exponentiated Exponential (EE), Beta Generalized Exponential (BGE), Exponentiated Weibull (EW), and Beta Inverse Weibull (BIW) were utilized for data analysis. The statistical model building criteria, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were used to measure the goodness of fit tests. Furthermore, we used the Bayesian approach to obtain the predictive survival inferences from the best-fit data based on the exponentiated Weibull model. Results: We identified the highest number of black non-Hispanic female breast cancer patients in Michigan and the lowest in Hawaii. The mean (SD), of age at diagnosis (years) was 58.3 (14.43). The mean (SD), of survival time (months) for black non-Hispanic females was 66.8 (30.20). Non-Hispanic blacks had a significantly increased risk of death compared to Black Hispanics (Hazard ratio: 1.96, 95%CI: 1.51-2.54). Compared to other statistical probability models, we found that the exponentiated Weibull model better fits for the survival times. By making use of the Bayesian method predictive inferences for future survival times were obtained. Conclusions: These findings will be of great significance in determining appropriate treatment plans and health-care cost allocation. Furthermore, the same approach should contribute to build future predictive models for any health related diseases.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.155-174
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• 2022

From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (