• Asian Pacific Journal of Cancer Prevention
• /
• 제16권15호
• /
• pp.6255-6259
• /
• 2015

Purpose: To evaluate the prognostic value of alkaline phosphatase (ALP) and gamma-glutamyltransferase (GGT) in gallbladder cancer (GBC). Materials and Methods: Serum ALP and GGT levels and clinicopathological parameters were retrospectively evaluated in 199 GBC patients. Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off values of ALP and GGT. Then, associations with overall survival were assessed by multivariate analysis. Based on the significant factors, a prognostic score model was established. Results: By ROC curve analysis, $ALP{\geq}210U/L$ and $GGT{\geq}43U/L$ were considered elevated. Overall survival for patients with elevated ALP and GGT was significantly worse than for patients within the normal range. Multivariate analysis showed that the elevated ALP, GGT and tumor stage were independent prognostic factors. Giving each positive factor a score of 1, we established a preoperative prognostic score model. Varied outcomes would be significantly distinguished by the different score groups. By further ROC curve analysis, the simple score showed great superiority compared with the widely used TNM staging, each of the ALP or GGT alone, or traditional tumor markers such as CEA, AFP, CA125 and CA199. Conclusions: Elevated ALP and GGT levels were risk predictors in GBC patients. Our prognostic model provides infomration on varied outcomes of patients from different score groups.

• 천문학회보
• /
• 제41권1호
• /
• pp.80.1-80.1
• /
• 2016

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, and true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model [Lee et al., 2012] which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 2011 to 2014 using this model. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. The forecast probability (y) is linearly changed with the cost/loss ratio (x) in the form of y=ax+b: a=0.88; b=0 (C), a=1.2; b=-0.05(M), a=1.29; b=-0.02(X). We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.536-0.853(C), 0.147-0.334(M), and 0.023-0.072(X). We expect that this study would provide a guideline to determine the probability threshold and the cost/loss ratio for space weather forecast.

• 한국컴퓨터정보학회논문지
• /
• 제24권1호
• /
• pp.41-47
• /
• 2019

In this paper, we propose a new batter evaluation model that reflects the skill of the opponent pitcher in Korean professional baseball. The model consists of evaluation factors such as Run Value, Contribution Score and Ball Consumption considering the pitcher grade. These evaluation factors are calculated as different data. In order to include the evaluation factors having different characteristics into one model, each evaluation factor is weighted and added. The genetic algorithms were used to calculate the weights, and the data were based on the 2016 records of Korea Professional Baseball and the salary data of the players of 2017. As a result of calculation of the weight, the weight of the Run Value was high and the weight of the Contribution Score was very low. This means that when calculating the annual salary, it reflects much of the expected score according to the batting result of the batter. On the other hand, the contribution score indicating the degree to which the batting result contributed to the victory of the team according to the state of the economy is not reflected in the salary or point system.

• 천문학회보
• /
• 제40권1호
• /
• pp.84.2-84.2
• /
• 2015

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model (Lee et al. 2012) which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 1996 to 2014 using this model. Overall frequencies are 61.08% (C), 22.83% (M), and 5.44% (X). The maximum probabilities computed by the model are 99.9% (C), 89.39% (M), and 25.45% (X), respectively. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. For the critical success index widely used, the probability threshold values for contingency tables are 25% (C), 20% (M), and 4% (X). We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.15-0.83(C), 0.11-0.51(M), and 0.04-0.17(X), also depending on a lifetime of satellite. We expect that this study would provide a guideline to determine the probability threshold for space weather forecast.

• Journal of Preventive Medicine and Public Health
• /
• 제32권4호
• /
• pp.538-545
• /
• 1999

Objective : To compare the predictive power of International Classification of Diseases 10th Edition(ICD-10) based International Classification of Diseases based Injury Severity Score(ICISS) with Trauma and Injury Severity Score(TRISS) and International Classification of Diseases 9th Edition Clinical Modification(ICD-9CM) based ICISS in the injury severity measure. Methods : ICD-10 version of Survival Risk Ratios(SRRs) was derived from 47,750 trauma patients from 35 Emergency Centers for 1 year. The predictive power of TRISS, the ICD-9CM based ICISS and ICD-10 based ICISS were compared in a group of 367 severely injured patients admitted to two university hospitals. The predictive power was compared by using the measures of discrimination(disparity, sensitivity, specificity, misclassification rates, and ROC curve analysis) and calibration(Hosmer-Lemeshow goodness-of-fit statistics), all calculated by logistic regression procedure. Results : ICD-10 based ICISS showed a lower performance than TRISS and ICD-9CM based ICISS. When age and Revised Trauma Score(RTS) were incorporated into the survival probability model, however, ICD-10 based ICISS full model showed a similar predictive power compared with TRISS and ICD-9CM based ICISS full model. ICD-10 based ICISS had some disadvantages in predicting outcomes among patients with intracranial injuries. However, such weakness was largely compensated by incorporating age and RTS in the model. Conclusions : The ICISS methodology can be extended to ICD-10 horizon as a standard injury severity measure in the place of TRISS, especially when age and RTS were incorporated in the model. In patients with intracranial injuries, the predictive power of ICD-10 based ICISS was relatively low because of differences in the classifying system between ICD-10 and ICD-9CM.

• 한국식품영양학회지
• /
• 제30권5호
• /
• pp.1058-1067
• /
• 2017

The purpose of this study was to develop the NCS-based cooking practice education method by using the full learning model and to confirm its effect. The study design was a pre-post test of the non-equality control group. The subjects of this study included 28 students in the experimental group and 27 students in the control group. The experimental group participated in the NCS-based cooking practice training using the complete learning model, and the control group received only cooking practice training based on the full learning model. The data were collected during the second semester of 2016 and analyzed by SPSS WIN 23.0. The results of this study were as follows: First, homogeneity test showed that pre - homogeneity such as general characteristics, cooking ability, and knowledge of cooking theory were achieved (p>0.05). Second, the experimental group recognized that its cooking ability was high. With respect to the ability to cook food, the ability to cook, and the ability to prepare food ingredients (p<0.01), personal hygiene management, cooking hygiene management, and cooking safety management abilities were not significant. The mean value the experimental group was high. Third, the final theoretical knowledge score was not significant. The average score in the experimental group (69 points) was 5 points higher than that in the control group (64 points). This was about two times higher than the score of 37 points in the first stage preliminary survey. Finally, the final performance score was significant (p<0.05), and the score in the experimental group (89 points) was 5 points higher than that in the control group (84 points). Therefore, the NCS-based cooking education method is confirmed to be an effective method, especially for improvement of the practical ability, improvement of theoretical knowledge, and achievement of perfect learning standards.

• 대한간호학회지
• /
• 제30권6호
• /
• pp.1531-1542
• /
• 2000

In this paper, we examined the depression of stroke patient's caregivers and analyzed influencing factors of the depression. The subjects were 215 caregivers who have takencare of stroke survivors in their home. The conceptual model of this study consisted of the caregiver's depression, perceived burden, illness intrusiveness, and patient's ADL. Modified Korean CES-D, modified subjective and objective Burden Scale, Illness intrusiveness(II), and Instrumental Activity of Daily Living(IADL) were used to measure concepts. Path analysis was used to test the model of this study. The results were as follows: 1. The mean depression score was 11.6 which was below the cut-off score of the CES-D. This score indicates that the subjects were higher than normal adults' mean score but not depressive. Eighty-six out of 215 caregivers(40%) were above the cut-off score. This finding was different from previous research results, and the reason might be the patients' capability of ADL. In a group of low capability patient's activities of daily living, caregiver's depression score was 15.5. 2. Caregiver's depression was positively related to caregiver's burden and illness intrusiveness, but negatively related to patient's activities of daily living. 3. The caregiver's perceived burden and illness intrusiveness directly influenced on their depression. Furthermore, the and caregiver's illness intrusiveness led to depression indirectly through their burden. A patient's activities of daily living didn't influence directly on depression but indirectly through caregiver's illness intrusiveness and burden.

• Journal of the Korean Data and Information Science Society
• /
• 제26권1호
• /
• pp.217-227
• /
• 2015

In observational study, handling confounders is a primary issue in measuring treatment effect of interest. Historically, a regression with covariate adjustment (covariate-adjusted regression) has been the typical approach to estimate treatment effect incorporating potential confounders into model. However, ever since the introduction of the propensity score, covariate-adjusted regression has been gradually replaced in medical literatures with various balancing methods based on propensity score. On the other hand, there is only a paucity of researches assessing propensity score methods compared with the covariate-adjusted regression. This paper examined the performance of propensity score methods in estimating risk difference and compare their performance with the covariate-adjusted regression by a Monte Carlo study. The study demonstrated in general the covariate-adjusted regression with variable selection procedure outperformed propensity-score-based methods in terms both of bias and MSE, suggesting that the classical regression method needs to be considered, rather than the propensity score methods, if a performance is a primary concern.

• 산업공학
• /
• 제24권4호
• /
• pp.323-329
• /
• 2011

We develop a stochastic model to predict the score of a soccer match. We describe the scoring process of the soccer match as a markovian arrival process (MAP). To do this, we define a two-state underlying Markov chain, in which the two states represent the offense and defense states of the two teams to play. Then, we derive the probability vector generating function of the final scores. Numerically inverting this generating function, we obtain the desired probability distribution of the scores. Sample numerical examples are given at the end to demonstrate how to utilize this result to predict the final score of the match.

• Journal of the Korean Data and Information Science Society
• /
• 제13권1호
• /
• pp.165-175
• /
• 2002

We consider the problem of estimating the change-point in mean change model with the one change-point. Lombard (1987) suggested change-point estimation based on score functions. Gombay and Huskova (1998) derived a class of change-point estimators with the score function of rank. Various change-point estimators with the log score functions of ranks are suggested and compared via simulation.