Journal of the Korean Data and Information Science Society
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v.24
no.6
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pp.1263-1274
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2013
VaR (value at risk), which represents the expectation of the worst loss that may occur over a period of time within a given level of confidence, is currently used by various financial institutions for the purpose of risk management. In the majority of previous studies, the probability of return has been modeled with normal distribution. Recently Chen et al. (2010) measured VaR with asymmetric Laplacian distribution. However, it is difficult to estimate the mode, the skewness, and the degree of variance that determine the shape of an asymmetric Laplacian distribution with limited data in the real-world market. In this paper, we show that the VaR estimated with (symmetric) Laplacian distribution model provides more accuracy than those with normal distribution model or asymmetric Laplacian distribution model with real world stock market data and with various statistical measures.
This study estimates the VSL(value of a statistical life) as well as the WTP(willingness to pay) for mortality risk reduction using sample selection model with data on liver cancer examination which is associated with little possibility of multi-purpose(i.e. joint production) in averting behavior. The marginal benefits of mortality risk reduction are estimated by applying for household production function model with medical expense and the time required for medical examination of liver cancer. Individuals are more likely to take liver cancer test if they are male, older, higher educated, those with spouse, smoker, more income of household, and more anxious about their health. The costs of liver cancer examination are statistically significantly affected with expected signs by size of mortality risk reduction, sex, period of eduction, those with spouse, and household income. The marginal effect of mortality risk reduction owing to taking liver cancer examination is estimated at 321,097 won. The costs of liver cancer examination are increased by 905 won with more one year of education period and by 1,743 won with more one million won in household income. On liver cancer examination, male spends more 12,310 won than female and those with spouse pay more 7,969 won than those without spouse. Therefore the VSL from mortality risk reduction due to liver cancer examination is 321.10 million won at mean size of mortality risk reduction and mean cost of liver cancer examination. The results of sensitivity tests on costs and effects of liver cancer test shows that the VSLs are estimated in a range from 160.55 million won to 642.19 million won.
Background: Although there are no biomarkers that are routinely used in endometrial cancer (EC) management, many studies have found that serum human epididymis protein 4 (HE4) is superior to cancer antigen 125 (CA125) in the detection of EC. The correlation of HE4 with two prognostic factors for EC, primary tumor diameter (PTD) and depth of myometrial invasion (DMI) may be useful in identifying EC patients at high risk of lymphatic dissemination. Objective: To evaluate the correlation of serum HE4 with PTD and DMI in patients with EC. Materials and Methods: A cross-sectional study was conducted on 70 EC patients who were scheduled for elective surgery at Rajavithi Hospital between 1st September 2013 and 30th May 2014. Preoperative serum levels of HE4 and CA125 were investigated, and then gross measurement of PTD was taken and postoperative pathologic slides were reviewed for DMI including histologic types, grading and staging. Results: Preoperative serum HE4 levels were strongly correlated with PTD (r=0.65, p<0.001) and moderately correlated with DMI (r=0.46, p<0.001). Moreover, serum HE4 levels were significantly elevated in EC patients with PTD >2 cm (p<0.001) and DMI > 50% (p=0.004). The performance of serum HE4 in identifying EC patients at low risk and high risk of lymph node metastasis was significantly better than that of CA125 (AUC 0.88 vs. 0.65, p=0.003). At an optimal cut-off value of 70 pM/L, serum HE4 had a sensitivity of 83.3% and a specificity of 80.0%. Conclusions: In EC patients, preoperative serum HE4 is significantly correlated with PTD and DMI. Serum HE4 levels could be useful in identifying endometrial cancer patients at high risk of lymphatic spread who would benefit from systemic lymphadenectomy at the cut-off value of 70 pM/L.
Background: An hCG regression curve has been used to predict the natural history and response to chemotherapy in gestational trophoblastic disease. We constructed hCG regression curves in high-risk gestational trophoblastic neoplasia (GTN) treated with EMA/CO and identified an optimal hCG level to detect EMA/CO resistance in GTN. Materials and Methods: Eighty-one women with GTN treated with EMA/CO were classified as primary high-risk GTN (n = 65) and single agent-resistance GTN (n = 16). The hCG levels prior to each course of chemotherapy were plotted in the 10th, 50th, and 90th percentiles to construct the hCG regression curves. Diagnostic performance was evaluated for an optimal cut-off value. Results: The median hCG levels were 264,482 mIU/mL mIU/mL and 495.5 mIU/mL mIU/mL for primary high-risk GTN and single agent-resistance GTN, respectively. The 50th percentile of the hCG level in primary high-risk GTN and single agent-resistance turned to normal before the 4th and the 2nd course of chemotherapy, respectively. The 90th percentile of the hCG level in primary high-risk GTN and single agent-resistance turned to normal before the 9th and the 2nd course of chemotherapy, respectively. The hCG level of ${\geq}118.6mIU/mL$ mIU/mL at the 5thcourse of EMA/CO predicted the EMA/CO resistance in primary high-risk GTN patients with a sensitivity of 85.7% and a specificity of 100%. Conclusion: EMA/CO resistance in primary high-risk GTN can be predicted by using an hCG regression curve in combination with the cut-off value of 118.6 mIU/mL at the 5thcourse of chemotherapy.
Objectives The purpose of this study is to propose a method to more specifically identify Sasang constitutional risk factors of metabolic syndromes by adjusting the cut-off value of Korea Sasang Constitutional Diagnostic Questionnaire (KS-15). Methods Data of 1997 participants in Korean medicine Daejeon Citizen Cohort study (KDCC) were analyzed. Metabolic syndrome was defined according to the NCEP-ATP III, lifestyle information, and hematologic information including KS-15 and demographic characteristics were used as covariates. Results The 179 subjects with metabolic syndrome accounted for 9.0% of the total. As a result of determining the Sasang constitution for the KS-15 response based on the cut-off values (approximate 0.33), 0.5, and 0.6 of the constitutional score, when performed at the 0.6 cut-off model, the odds ratio of TE was 2.46 which showed a statistically significantly higher risk than the borderline group. For the accuracy of the model and the Area under the curve (AUC), the model accuracy based on the original cut-off of the KS-15 was 0.902 and AUC was 0.737. The accuracy of the model with cut-off of 0.5 and with of 0.6 were 0.904 and 0.902, respectively, and the AUCs were 0.687 and 0.741, respectively. Conclusion In this study, we confirmed that it is effective to increase the cut-off value of KS-15 to 0.6 in the metabolic syndrome risk model. It is expected that this could increase the accuracy of identifying high-risk groups for metabolic syndrome.
Public concerns about hazardous health effect from the exposure to organic by-products of the chlorination have been increased. There are numerous studies reporting that chlorination of drinking water produces numerous chlorinated organic by-products including THMs, HAAs, HANs. Some of these products are known to be animal carcinogens. The purpose of this study was to estimate health risk of DBPs by chlorinated drinking water ingestion in Seoul based on methodologies that have been developed for conducting risk assessment of complex-chemical-mixture. The drinking water sample was collected seperately at six water treatment plant in Seoul at March, April, 1996. In tap water of households in Seoul, DBPs were measured wilfh the mean value of 36.6 $\mu$g/L. Risk assessment processes,. which include processes for the estimation of human cancer potency using animal bioassay data and calculation of human exposure, entail uncertainties. In the exposure assessment process, exposure scenarios with various assumptions could affect the exposure amount and excess cancer risk. The reference dose of haloacetonitriles was estimated to be 0.0023 mg/kg/day by applying dibromoacetonitrile NOAEL and uncertainty factor to the mean concentration. In the first case, human excess cancer risk was estimated by the US EPA method used to set the MCL (maximum contaminant level). In the second and third case, the risk was estimated for multi-route exposure with and without adopting Monte-Carlo simulation, respectively. In the second case, exposure input parameters and cancer potencies used probability distributions, and in the third case, those values used point estimates (mean, and maximum or 95% upper-bound value). As a result, while the excess cancer risk estimated by US EPA method considering only direct ingestion tended to be underestimated, the risk which was estimated by considering multi-route exposure without Monte-Carlo simulation and then using the maximum or 95% upper-bound value as input parameters tended to be overestimated. In risk assessment for Trihalomethanes, considering multi-route exposure with adopting Monte-Carlo analysis seems to provide the most reasonable estimations.
Journal of the Korean Society of Marine Environment & Safety
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v.23
no.5
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pp.447-454
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2017
Using two large coast guard ships at sea, we created four encounter situations ($000^{\circ}$, $045^{\circ}$, $090^{\circ}$, $135^{\circ}$) with high possibility of collision, from 3 NM up to 0.25 NM. As relative distance was gradually decreased, the subjects were measured at 0.25 NM intervals and perceived ship collision risk (PSCR) was determined by looking at the opponent ship. Characteristics were statistically analyzed using the obtained data. The purpose of this study was to analyze the characteristics of collision risk values obtained from twelve intervals, from 3 NM to 0.25 NM relative to encounter situations by curve fitting with appropriate polynomials, to determine the distance from which the change in perceived collision risk is greatest. As a result, an optimal regression equation for each distance interval was derived from each analysis direction. The greatest variation in average collision risk value was over the range 1.25 ~ 1 NM, and the collision risk value was largest at 1 NM. The maximum change in perceived collision risk was at 1 NM. These results can contribute to preventive guidelines to minimize human error in close proximity situations with a high probability of ship collision.
Purpose: The purpose of the study was to validate fall risk assessment scales among hospitalized adult patients in South Korea using the electronic medical records by comparing sensitivity, specificity, positive predictive values, and negative predictive values of Morse Fall Scale (MFS), Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS), and Johns Hopkins Hospital Fall Risk Assessment tool (JHFRAT). Methods: A total of 120 patients who experienced fall episodes during their hospitalization from June 2010 to December 2013 was categorized into the fall group. Another 120 patients, who didn't experience fall episodes with age, sex, clinical departments, and the type of wards matched with the fall group, were categorized to the comparison group. Data were analyzed for the comparisons of sensitivity, specificity, positive and negative predictive values, and the area under the curve of the three tools. Results: MFS at a cut-off score of 48 had .806 for ROC curves, 76.7% for sensitivity, 77.5% for specificity, 77.3% for positive predictive value, and 76.9% for negative predictive value, which were the highest values among the three fall assessment scales. Conclusion: The MFS with the highest score and the highest discrimination was evaluated to be suitable and reasonable for predicting falls of inpatients in med-surg units of university hospitals.
Ga Young Yoo;Seung Keun Yoon;Mi Hyoung Moon;Seok Whan Moon;Wonjung Hwang;Kyung Soo Kim
Journal of Chest Surgery
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v.57
no.3
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pp.302-311
/
2024
Background: Unexpected conversion to thoracotomy during planned video-assisted thoracoscopic surgery (VATS) can lead to poor outcomes and comparatively high morbidity. This study was conducted to assess preoperative risk factors associated with unexpected thoracotomy conversion and to develop a risk scoring model for preoperative use, aimed at identifying patients with an elevated risk of conversion. Methods: A retrospective analysis was conducted of 1,506 patients who underwent surgical resection for non-small cell lung cancer. To evaluate the risk factors, univariate analysis and logistic regression were performed. A risk scoring model was established to predict unexpected thoracotomy conversion during VATS of the lung, based on preoperative factors. To validate the model, an additional cohort of 878 patients was analyzed. Results: Among the potentially significant clinical variables, male sex, previous ipsilateral lung surgery, preoperative detection of calcified lymph nodes, and clinical T stage were identified as independent risk factors for unplanned conversion to thoracotomy. A 6-point risk scoring model was developed to predict conversion based on the assessed risk, with patients categorized into 4 groups. The results indicated an area under the receiver operating characteristic curve of 0.747, with a sensitivity of 80.5%, specificity of 56.4%, positive predictive value of 1.8%, and negative predictive value of 91.0%. When applied to the validation cohort, the model exhibited good predictive accuracy. Conclusion: We successfully developed and validated a risk scoring model for preoperative use that can predict the likelihood of unplanned conversion to thoracotomy during VATS of the lung.
Journal of The Korean Society of Agricultural Engineers
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v.55
no.4
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pp.73-82
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2013
The main objective of this study was to evaluate Representative Concentration Pathways (RCP) scenarios-based flood risk at a Si-Gun level. A bias correction using a quantile mapping method with the Generalized Extreme Value (GEV) distribution was performed to correct future precipitation data provided by the Korea Meteorological Administration (KMA). A series of proxy variables including CN80 (Number of days over 80 mm) and CX3h (Maximum precipitation during 3-hr) etc. were used to carry out flood risk assessment. Indicators were normalized by a Z-score method and weighted by factors estimated by principal component analysis (PCA). Flood risk evaluation was conducted for the four different time periods, i.e. 1990s, 2025s, 2055s, and 2085s, which correspond to 1976~2005, 2011~2040, 2041~2070, and 2071~2100. The average flood risk indices based on RCP4.5 scenario were 0.08, 0.16, 0.22, and 0.13 for the corresponding periods in the order of time, which increased steadily up to 2055s period and decreased. The average indices based on RCP8.5 scenario were 0.08, 0.23, 0.11, and 0.21, which decreased in the 2055s period and then increased again. Considering the average index during entire period of the future, RCP8.5 scenario resulted in greater risk than RCP4.5 scenario.
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