• Journal of Preventive Medicine and Public Health
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• 제43권1호
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• pp.42-49
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• 2010

Objectives: To compare the performance of three International Statistical Classification of Diseases, 10th Revision translations of the Charlson comorbidities when predicting in-hospital among patients with myocardial infarction (MI). Methods: MI patients ${\geq}20$ years of age with the first admission during 2006 were identified(n=20,280). Charlson comorbidities were drawn from Heath Insurance Claims Data managed by Health Insurance Review and Assessment Service in Korea. Comparisions for various conditions included (a) three algorithms (Halfon, Sundararajan, and Quan algorithms), (b) lookback periods (1-, 3- and 5-years), (c) data range (admission data, admission and ambulatory data), and (d) diagnosis range (primary diagnosis and first secondary diagnoses, all diagnoses). The performance of each procedure was measured with the c-statistic derived from multiple logistic regression adjusted for age, sex, admission type and Charlson comorbidity index. A bootstrapping procedure was done to determine the approximate 95% confidence interval. Results: Among the 20,280 patients, the mean age was 63.3 years, 67.8% were men and 7.1% died while hospitalized. The Quan and Sundararajan algorithms produced higher prevalences than the Halfon algorithm. The c-statistic of the Quan algorithm was slightly higher, but not significantly different, than that of other two algorithms under all conditions. There was no evidence that on longer lookback periods, additional data, and diagnoses improved the predictive ability. Conclusions: In health services study of MI patients using Health Insurance Claims Data, the present results suggest that the Quan Algorithm using a 1-year lookback involving primary diagnosis and the first secondary diagnosis is adequate in predicting in-hospital mortality.

• 대한치매학회지
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• 제22권4호
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• pp.121-129
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• 2023

Background and Purpose: As it becomes an aging society, interest in senile diseases is increasing. Alzheimer's dementia (AD) and osteoporosis are representative senile diseases. Various studies have reported that AD and osteoporosis share many risk factors that affect each other's incidence. This aimed to determine if active medication treatment of AD could affect the development of osteoporosis. Methods: The Health Insurance Review and Assessment Service provided data consisting of diagnosis, demographics, prescription drug, procedures, medical materials, and healthcare resources. In this study, data of all AD patients in South Korea who were registered under the national health insurance system were obtained. The cohort underwent conversion to an Observational Medical Outcomes Partnership-Common Data Model version 5 format. Results: This study included 11,355 individuals in the good persistent group and an equal number of 11,355 individuals in the poor persistent group from the National Health Claims database for AD drug treatment. In primary analysis, the risk of osteoporosis was significantly higher in the poor persistence group than in the good persistence group (hazard ratio, 1.20 [95% confidence interval, 1.09-1.32]; p<0.001). Conclusions: We found that the good persistence group treated with anti-dementia drugs for AD was associated with a significant lower risk of osteoporosis in this nationwide study. Further studies are needed to clarify the pathophysiological link in patients with two chronic diseases.

• Communications for Statistical Applications and Methods
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• 제26권2호
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• pp.103-129
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• 2019

The main goal of a case-control study is to learn the association between various risk factors and a primary outcome (e.g., disease status). Particularly recently, it is also quite common to perform secondary analyses of the case-control data in order to understand certain associations between the risk factors of the primary outcome. It has been repeatedly documented with case-control data, association studies of the risk factors that ignore the case-control sampling scheme can produce highly biased estimates of the population effects. In this article, we review the issues of the naive secondary analyses that do not account for the biased sampling scheme, and also the various methods that have been proposed to account for the case-control ascertainment. We additionally compare the results of many of the discussed methods in an example examining the association of a particular genetic variant with smoking behavior, where the data were obtained from a lung cancer case-control study.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.110-116
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• 2023

Data confidentiality refers to the characteristic that information kept undisclosed or hidden from unauthorized parties. It considered a key security requirement in current supply chain management (SCM) systems. Currently, academia and industry tend to adopt blockchain and IoT technologies in order to develop efficient and secure SCM systems. However, providing confidential data sharing among these technologies is quite challenging due to the limitations associated with blockchain and IoT devices. This review paper illustrates the importance of preserving data confidentiality in SCM systems by highlighting the state of the art on confidentiality-preserving methodologies in the context of blockchain based IoT-SCM systems and the challenges associated with it.

• 지능정보연구
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• 제29권2호
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• pp.35-56
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• 2023

정보통신 기술의 발전에 따라 웹 사이트에는 수많은 리뷰가 지속적으로 게시되고 있다. 이로 인해 정보 과부하 문제가 발생하여 사용자들은 본인이 원하는 리뷰를 탐색하는데 어려움을 겪고 있다. 따라서, 이러한 문제를 해결하여 사용자에게 유용하고 신뢰성 있는 리뷰를 제공하기 위해 리뷰 유용성 예측에 관한 연구가 활발히 진행되고 있다. 기존 연구는 주로 리뷰에 포함된 특성을 기반으로 리뷰 유용성을 예측하였다. 그러나, 예측한 리뷰가 왜 유용한지 근거를 제시할 수 없다는 한계점이 존재한다. 따라서 본 연구는 이러한 한계점을 해결하기 위해 리뷰 유용성 예측 모델에 eXplainable Artificial Intelligence(XAI) 기법을 적용하는 방법론을 제안하였다. 본 연구는 Yelp.com에서 수집한 레스토랑 리뷰를 사용하여 리뷰 유용성 예측에 관한 연구에서 널리 사용되는 6개의 모델을 통해 예측 성능을 비교하였다. 그 다음, 예측 성능이 가장 우수한 모델에 XAI 기법을 적용하여 설명 가능한 리뷰 유용성 예측 모델을 제안하였다. 따라서 본 연구에서 제안한 방법론은 사용자의 구매 의사결정 과정에서 유용한 리뷰를 추천할 수 있는 동시에 해당 리뷰가 왜 유용한지에 대한 해석을 제공할 수 있다.

• Journal of Information Technology Applications and Management
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• 제27권6호
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• pp.53-73
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• 2020

Many prior studies have been conducted that positive reviews increase the intention to purchase. However, there are very few papers that have studied the impact of review search on purchase satisfaction. It is meaningful to study the impact of review search on purchase satisfaction as it can lead the business successfully by inducing repurchase. There is also no study of how review search have different effects on purchase satisfaction among countries. Given the growing number of cross-border e-commerce, we believe that the need for research is high because identifying these differences between countries can have a very important impact on a company's successful overseas expansion. Therefore, in this study, the impact of positive and negative review search on purchase satisfaction and the national impact were set up as a research model. In order to verify this research model, the survey was distributed to those who experienced online purchase in Korea and China, and a total of 234 copies were collected, including 125 copies in Korea, 109 copies in China, and the research model was verified using Smart-PLS structural equation analysis tools. First, positive review search has been shown to positively affect purchase satisfaction. Second, it has been shown that negative review search also has a positive effect on purchase satisfaction. Third, the impact of positive and negative review search on purchase satisfaction was different between Korea and China. While Korea is more aggressive in review search than China due to its high tendency to avoid uncertainty, China is less likely to avoid uncertainty than Korea and is more likely to rely on brand familiarity. Therefore, according to the uncertainty avoidance moderation effect the impact of positive and negative review search on purchase satisfaction was higher in Korea than in China. In this study, Shopping mall managers need to take strategic measures to maximize shopping mall performance by recognizing positive aspects of negative review search on purchase satisfaction. Companies and managers in Korea and China can establish strategies to promote product sales when companies enter the global market.

• Asian Pacific Journal of Cancer Prevention
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• 제16권14호
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• pp.6033-6038
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• 2015

Background: Experience of lung cancer includes negative impacts on both physical and psychological health. Pain is one of the negative experiences of lung cancer. Cognitive behavioral therapy techniques are often recommended as treatments for lung cancer pain. The objective of this review was to synthesize the evidence on the effectiveness of cognitive behavioral therapy techniques in treating lung cancer pain. This review considered studies that included lung cancer patients who were required to 1) be at least 18 years old; 2) speak and read English or Thai; 3) have a life expectancy of at least two months; 4) experience daily cancer pain requiring an opioid medication; 5) have a positive response to opioid medication; 6) have "average or usual" pain between 4 and 7 on a scale of 0-10 for the day before the clinic visit or for a typical day; and 7) able to participate in a pain evaluation and treatment program. This review considered studies to examine interventions for use in treatment of pain in lung cancer patients, including: biofeedback, cognitive/attentional distraction, imagery, hypnosis, and meditation. Any randomized controlled trials (RCTs) that examined cognitive behavioral therapy techniques for pain specifically in lung cancer patients were included. In the absence of RCTs, quasi-experimental designs were reviewed for possible conclusion in a narrative summary. Outcome measures were pain intensity before and after cognitive behavioural therapy techniques. The search strategy aimed to find both published and unpublished literature. A three-step search was utilised by using identified keywords and text term. An initial limited search of MEDLINE and CINAHL was undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe the article. A second search using all the identified keywords and index terms was then undertaken across all included databases. Thirdly, the reference list of all identified reports and articles were searched for additional studies. Searches were conducted during January 1991- March 2014 limited to English and Thai languages with no date restriction. Materials and Methods: All studies that met the inclusion criteria were assessed for methodological quality by three reviewers using a standardized critical appraisal tool from the Joanna Briggs Institute (JBI). Three reviewers extracted data independently, using a standardized data extraction tool from the Joanna Briggs Institute (JBI). Ideally for quantitative data meta-analysis was to be conducted where all results were subject to double data entry. Odds ratios (for categorical data) and weighted mean differences (for continuous data) and their 95% confidence intervals were to be calculated for analysis and heterogeneity was to be assessed using the standard Chi-square. Where statistical pooling was not possible the finding were be presented in narrative form. Results: There were no studies located that met the inclusion requirements of this review. There were also no text and opinion pieces that were specific to cognitive behavioral therapy techniques pain and lung cancer patients.Conclusions: There is currently no evidence available to determine the effectiveness of cognitive behavioural therapy techniques for pain in lung cancer patients.

• 경영정보학연구
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• 제23권3호
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• pp.51-75
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• 2021

세계적인 전자상거래 기업들은 지속 가능한 경쟁력을 확보하기 위해 사용자 맞춤형 추천 서비스를 제공하고 있다. 기존 관련 연구에서는 주로 평점, 구매 여부 등 정량적 선호도 정보를 사용하여 개인화 추천 서비스를 제공하였다. 하지만 이와 같은 정량적 선호도 정보를 사용하여 개인화 추천 서비스를 제공하면 추천 성능이 저하될 수 있다는 문제점이 제기되고 있다. 호텔을 이용한 사용자가 호텔 서비스, 청결 상태 등에 대하여 만족하지 못한다고 리뷰를 작성하였으나 선호도 평점 5점을 부여했을 때 정량적 선호도(평점)와 정성적 선호도(리뷰)가 불일치한 문제가 발생할 수 있다. 따라서 본 연구에서는 정량적 선호도 정보와 정성적 선호도 정보가 일치하는지를 확인하고 이를 바탕으로 선호도 정보가 일치하는 사용자를 바탕으로 새로운 프로파일을 구축하여 개인화 추천 서비스를 제공하고자 한다. 리뷰에서 정성적 선호도를 추출하기 위해 자연어 처리 관련 연구에서 널리 사용되고 있는 CNN, LSTM, CNN + LSTM 등 딥러닝 기법을 사용하여 감성분석 모델을 구축하였다. 이를 통해 사용자가 작성한 리뷰에서 정성적 선호도 정보를 정교하게 추출하여 정량적 선호도 정보와 비교하였다. 본 연구에서 제안한 추천 방법론의 성능을 평가하기 위해 세계 최대 여행 플랫폼 TripAdvisor에서 실제 호텔을 이용한 사용자 선호도 정보를 수집하여 사용하였다. 실험 결과 본 연구에서 제안한 추천 방법론이 기존의 정량적 선호도만을 고려하는 추천 방법론보다 우수한 추천 성능을 나타냄을 확인할 수 있었다.

• 유통과학연구
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• 제12권7호
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• pp.89-101
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• 2014

Purpose - This study aims to show that consignments can enable supply chain collaboration, based on the review of selected studies, and aims to investigate its potential to be a better collaboration program, through an analytical comparison with other collaboration initiatives. Research design, data, and methodology - This study uses a literature review on selected studies that researched consignments. In addition, based on the proposed framework, the current consignment process and other well-known collaboration programs are analyzed in terms of three key collaboration aspects. Results - Most studies employ simple research in terms of their purpose and methodology. An analysis with the proposed framework indicates the potential of consignments to foster supply chain collaboration. Conclusions - Based on the literature review, this study suggests that future research needs to aim for diverse research goals and conduct sophisticated research on consignments. An analysis with the proposed framework shows that consignments would be more effective for supply chain collaboration if active information sharing and joint decision-making are implemented.

• 보건행정학회지
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• 제27권1호
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• pp.30-38
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• 2017

Background: This study aims to analyze the behavioral changes of healthcare providers and influencing factors after the reviewer unification of auto insurance medical benefit claims by an independent review agency. Methods: The comparison data were collected from the second half of 2013 and the same period of 2014. The key indicators are the number of admission days, the number of outpatient visits, inpatient ratio, inpatient medical expenses, and outpatient medical expenses. Results: Four indicators (number of admission days, number of outpatient visits, inpatient ratio, and outpatient medical expenses) showed statistically significant drops, while one indicator (inpatient medical expenses) showed no significant change. Conclusion: The reviewer unification of auto insurance medical benefit claims by an independent review agency showed significant reduction in cost and patient days.