• Clinical and Experimental Pediatrics
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• v.51 no.11
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• pp.1158-1164
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• 2008

Purpose : To investigate the discriminative ability of pediatric index of mortality 2 (PIM2) and pediatric risk of mortality III (PRISM III) in predicting mortality in children admitted into the intensive care unit (ICU). Methods : We retrospectively analyzed variables of PIM2 and PRISM III based on medical records with children cared for in a single hospital ICU from January 2003 to December 2007. Exclusions were children who died within 2 h of admission into ICU or hopeless discharge. We used Students t test and ANOVA for general characteristics and for correlation between survivors and non-survivors for variables of PIM2 and PRISM III. In addition, we performed multiple logistic regression analysis for Hosmer-Lemeshow goodness-of-fit, receiver operating characteristic curve (ROC) for discrimination, and calculated standardized mortality ratio (SMR) for estimation of prediction. Results : We collected 193 medical records but analyzed 190 events because three children died within 2 h of ICU admission. The variables of PIM2 correlated with survival, except for the presence of post-procedure and low risk. In PRISM III, there was a significant correlation for cardiovascular/neurologic signs, arterial blood gas analysis but not for biochemical and hematologic data. Discriminatory performance by ROC showed an area under the curve 0.858 (95% confidence interval; 0.779-0.938) for PIM2, 0.798 (95% CI; 0.686-0.891) for PRISM III, respectively. Further, SMR was calculated approximately as 1 for the 2 systems, and multiple logistic regression analysis showed ${\chi}^2(13)=14.986$, P=0.308 for PIM2, ${\chi}^2(13)=12.899$, P=0.456 for PRISM III in Hosmer-Lemeshow goodness-of-fit. However, PIM2 was significant for PRISM III in the likelihood ratio test (${\chi}^2(4)=55.3$, P<0.01). Conclusion : We identified two acceptable scoring systems (PRISM III, PIM2) for the prediction of mortality in children admitted into the ICU. PIM2 was more accurate and had a better fit than PRISM III on the model tested.

• Journal of the Korean Society of Radiology
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• v.83 no.1
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• pp.112-126
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• 2022

Purpose To determine the value of 3 Tesla (T) MRI texture analysis for predicting tumor margin infiltration in soft tissue sarcomas. Materials and Methods Thirty-one patients who underwent 3T MRI and had a pathologically confirmed diagnosis of soft tissue sarcoma were included in this study. Margin infiltration on pathology was used as the gold standard. Texture analysis of soft tissue sarcomas was performed on axial T1-weighted images (WI) and T2WI, fat-suppressed contrast-enhanced (CE) T1WI, diffusion-weighted images (DWI) with b-value of 800 s/mm², and apparent diffusion coefficient (ADC) was mapped. Quantitative parameters were compared between sarcomas with infiltrative margins and those with circumscribed margins. Results Among the 31 patients with soft tissue sarcomas, 23 showed tumor margin infiltration on pathology. There were significant differences in kurtosis with the spatial scaling factor (SSF) of 0 and 6 on T1WI, kurtosis (SSF, 0) on CE-T1WI, skewness (SSF, 0) on DWI, and skewness (SSF, 2, 4) on ADC between sarcomas with infiltrative margins and those with circumscribed margins (p ≤ 0.046). The area under the receiver operating characteristic curve based on MR texture features for identification of infiltrative tumor margins was 0.951 (p < 0.001). Conclusion MR texture analysis is reliable and accurate for the prediction of infiltrative margins of soft tissue sarcomas.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.619-630
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• 2019

Dyslipidemia is a representative chronic disease affecting Koreans that requires continuous management. It is also a known risk factor for cardiovascular disease such as hypertension and diabetes. However, it is difficult to diagnose vascular disease without a medical examination. This study identifies risk factors for the recognition and prevention of dyslipidemia. By integrating them, we construct a statistical instrumental nomogram that can predict the incidence rate while visualizing. Data were from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. First, a chi-squared test identified twelve risk factors of dyslipidemia. We used a naïve Bayesian classifier model to construct a nomogram for the dyslipidemia. The constructed nomogram was verified using a receiver operating characteristics curve and calibration plot. Finally, we compared the logistic nomogram previously presented with the Bayesian nomogram proposed in this study.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.33-41
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• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

• Clinical and Experimental Reproductive Medicine
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• v.35 no.4
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• pp.309-317
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• 2008

Objectives: The aim of this study was to evaluate the usefulness of Anti-mullerian hormone (AMH) as a predictive marker for ovarian response and cycle outcome in IVF cycles. Methods: From Jan., to Aug., 2007, 111 patients undergoing IVF/ICSI stimulated by short or antagonist protocol were selected. On cycle day 3, basal serum AMH level and FSH level were measured. The correlation between basal serum AMH or FSH, and COH outcome was analyzed and IVF outcome was compared according to the AMH levels. To determine the threshold value of AMH for poor- and hyper-response, ROC curve was analyzed. Results: Serum AMH showed higher correlation coefficient (r=0.792, p<0.001) with the number of retrieved mature oocyte than serum FSH (r=-0.477, p<0.001). According to ovarian response, FSH and AMH leves showed significant differences among poor, normal, and hyperresponder. For predicting poor (${\leq}2$ oocytes) and hyperresponse (${\geq}17$ oocyets), AMH cut-off values were 0.5 ng/ml (the sensitivity 88.9% and the specificity 89.5%) and 2.5 ng/ml (sensitivity 85.7%, specificity 87.0%), respectively. According to the AMH level, patients were divided into 3 groups: low (${\leq}0.60\;ng/ml$), normal ($0.60{\sim}2.60\;ng/ml$), and high AMH (${\geq}2.60\;ng/ml$). The number of retrieved mature oocytes was significantly higher ($2.7{\pm}2.2$, $8.1{\pm}4.8$, $16.5{\pm}5.7$) and total gonadotropin dose was lower ($3530.5{\pm}1251.0$, $2957.1{\pm}1057.6$, and $2219.2{\pm}751.9\;IU$) in high AMH group (p<0.001). There was no significant difference in fertilization rates and pregnancy rates (23.8%, 34.0%, 37.5%) among the groups. Conclusions: Basal serum AMH level correlated better with the number of retrieved mature oocytes than FSH level, suggesting its usefulness for predicting ovarian response. However, IVF outcome was not significantly different according to the AMH levels. Serum AMH level presented good cut-off value for poor- or hyper-responders, therefore it could be useful in prediction of cycle cancellation, gonadotropin dose, and OHSS risk in IVF cycles.

• Journal of radiological science and technology
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• v.32 no.1
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• pp.69-78
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• 2009

The cardiovascular disease has been known as a common cause of death for a long time in the west. The eating habits of Asia, including Korea, have changed recently, so that this disease is also a problem in Asia now. Annual Report on the Cause of Death Statistics from 1996 to 2006 reported that the cardiovascular disease would become the number one cause of death in the next $5{\sim}10$ years. Therefore we realize that more accurate examination is required. The aim of this study was to investigate the accuracy of Calcium-scoring CT and the relationship between risk factor and quantitative scores of Calcium-scoring CT. Through this study we expect that the national public health will be improved. Seventy patients with chest pain were chosen at random. The patients were undergone both coronary CT antigraphy and Calcium - scoring CT at G hospital in Incheon from February 1 to June 30, 2008. The result of the Calcium-scoring CT showed its usefulness for Ischemic cardiovascular disease, with an accuracy similar to that of exercise/pharmacologic stress or ECG when it is difficult for a patient to exercise due to joint problems, aging or for other reasons.

• Journal of the Korean Society of Radiology
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• v.12 no.2
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• pp.217-223
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• 2018

This study to search the diagnostic performance of shear wave elastography(SWE) in breast mass and to compare the biopsy result and stiffness obtained from shear wave elastography. Diagnostic breast ultrasonography and SWE were targeted for 157 patients who had breast ultrasonography was diagnosed mass from June 2017 to September 2017. Pathology results of 157 patients showed a benign 92 patients(Age, $44.54{\pm}11.84$) and a malignancy 65 patients(Age, $51.55{\pm}10.54$). Final evaluation, biopsy result, and quantitative SWE result were obtained and compared with each other according to Breast Imaging Reporting and Data System(BI-RADS) of diagnostic breast ultrasonography. Quantitative SWE value and pathologic result showed the highest diagnostic specificity of 83.70% in Emean and sensitivity of 89.23% in Emin. Quantitative SWE result and biopsy result is statistically significant.(p=0.000). The optimal cut-off value for malignant lesions was 66.3 kPa and 63.7 kPa, respectively, for the sensitivity, specificity, high maximum mean elasticity value(Emax) and mean elasticity value(Emean) and this showed the highest diagnostic area under the ROC curve(Az) value compared to other SWE measurement(p=0.000). The addition of SWE to conventional US in breast mass make a increase diagnostic specificity and reduce unnecessary biopsy. Therefore, it is expected that it will be helpful to analyze the breast mass using the above analysis and apparatus.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.617-629
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• 2020

In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.

• Journal of Chest Surgery
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• v.39 no.10 s.267
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• pp.749-753
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• 2006

Background: The purpose of this study is to assess a score system for operative risk evaluation of CABG. Material and Method: From January 2001 to September 2005, retrospective study for various perioperative factors of 2993 cases was done. Result: The early operative mortality was 2.4% and the beta coefficients of 7 core variables related to it (preoperative LV dysfuction, preoperative renal failure, MI within 1 week, reoperation, combined surgery, preoperative atrial fibrillation, preoperative IABP) were adjusted to score system. ROC curve and Hosmer and Lemeshow goodness of fit test was done. Conclusion: This score system was effective in assessing operative risk of CABG. But It is necessary to gather larger volume of case and perform multicenter study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.397-411
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• 2023

The number of deteriorated bridges with a service period of more than 30 years has been rapidly increasing in Korea. Accordingly, the importance of advanced maintenance technologies through the predictions of age-induced deterioration degree, condition, and performance of bridges is more and more noticed. The prediction method of the safety grade of bridges was proposed in this study using the classification models of the Decision Tree and the Random Forest based on machine learning. As a result of analyzing these models for the 8,850 bridges located in national roads with various evaluation indexes such as confusion matrix, balanced accuracy, recall, ROC curve, and AUC, the Random Forest largely showed better predictive performance than that of the Decision Tree. In particular, random under-sampling in the Random Forest showed higher predictive performance than that of other sampling techniques for the C and D grade bridges, with the recall of 83.4%, which need more attention to maintenance because of the significant deterioration degree. The proposed model can be usefully applied to rapidly identify the safety grade and to establish an efficient and economical maintenance plan of bridges that have not recently been inspected.