• 한국도로학회논문집
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• 제20권2호
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• pp.35-44
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• 2018

PURPOSES : The purpose of this research is to analyze the characteristics of panels that affect the evaluating results of riding quality and to evaluate the appropriateness of roughness management criteria based on ride comfort satisfaction. METHODS : In order to analyze the influence of panel characteristics of riding quality, 33 panels, consisting of civilians and experts, were selected. Also, considering the roughness distribution of the expressway, 35 sections with MRI ranging from 1.17 m/km to 4.65 m/km were selected. Each panel boarded a passenger car and evaluated the riding quality with grades from 0 to 10, and assessed whether it was satisfied or not. After removing outlier results using a box plot technique, 964 results were analyzed. An ANOVA was conducted to evaluate the effects of panel expertise, age, driving experience, vehicle ownership, and gender on the evaluation results. In addition, by using the receiver operating characteristics (ROC) curve, the MRI value, which can most accurately evaluate the satisfaction with riding quality, was derived. Then, the compatibility of MRI was evaluated using AUC as a criterion to assess whether the riding quality was satisfactory. RESULTS : Only the age of the panel participants were found to have an effect on the riding quality satisfaction. It was found that satisfaction with riding quality and MRI are strongly correlated. The satisfaction rate of roughness management criteria on new (MRI 1.6 m/km) and maintenance (MRI 3.0 m/km) expressways were 95% and 53%, respectively. As a result of evaluating the roughness management criteria by using the ROC curve, it was found that the accuracy of satisfaction was the highest at MRI 3.1-3.2 m/km. In addition, the AUC of the MRI was about 0.8, indicating that the MRI was an appropriate index for evaluating the riding quality satisfaction. CONCLUSIONS : Based on the results, the distribution of the panels' age should be considered when panel rating is conducted. From the results of the ROC curve, MRI of 3.0 m/km, which is a criterion of roughness management on maintenance expressways, is considered as appropriate.

• Journal of Korean Neurosurgical Society
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• 제67권1호
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• pp.94-102
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• 2024

Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.

• 보건행정학회지
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• 제30권3호
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• pp.355-365
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• 2020

Background: This study is aimed to verify individual and regional-level factors affecting the depression of Koreans and to develop social programs for improving the depressive status. Methods: This study used individual-level variables from the Korean Community Health Survey (2018) and used the e-regional index of the Korean Statistical Information Service as the regional-level variable. A multi-level logistic regression was executed to identify individual and regional-level variables that were expected to affect the extent of depressive symptoms and to draw the receiver operating characteristic curve to compare the volume of impact between variables from both levels. Results: The results of the multi-level logistic regression analysis in regards to individual-level factors showed that older age, female gender, a lower income level, a lower education level, not having a spouse, the practice of walking, the consumption of breakfast higher levels of stress, and having high blood pressure or diabetes were associated with a greater increase in depressive symptoms. In terms of regional factors, areas with fewer cultural facilities and fewer car registration had higher levels of depressive symptoms. The comparison of area under the curve showed that individual factors had a greater influence than regional factors. Conclusion: This study showed that while both, individual and regional-level factors affect depression, the influence of the latter was relatively weaker as compared to the first. In this sense, it is necessary to develop programs focused on the individual, such as social prescribing at the local or community-level, rather than the city and nation-level approach that are currently prevalent.

• 응용통계연구
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• 제31권5호
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• pp.573-585
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• 2018

본 연구에서는 제 2형 당뇨(type 2 diabetes mellitus)의 발병 확률을 예측하기 위해 11가지 위험요인을 가지고 로지스틱 회귀모형과 순수 베이지안 분류기 모형에 적합시킨다. 그런 다음 이를 시각적으로 쉽게 이해하는데 도움을 주는 노모그램 구축 방법을 소개한다. 분석은 2013-2015년 6기 국민건강영양조사 데이터를 가지고 분석하였다. 또 로지스틱 회귀모형에 세 가지 상호작용 항을 넣어 분석의 질을 높이고자 하였고 베이지안 노모그램에 left-aligned 방법을 사용하여 비교하기 쉽게 만들었다. 최종적으로 두 노모그램을 비교하고 효용성을 알아보았다. 마지막으로 ROC 곡선을 이용하여 노모그램이 적절한지 검증하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권2호
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• pp.707-712
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• 2015

Background: To evaluate use of magnetic resonance imaging (MRI) and a logistic model including risk factors for lymph node metastasis for improved diagnosis. Materials and Methods: The subjects were 176 patients with rectal cancer who underwent preoperative MRI. The longest lymph node diameter was measured and a cut-off value for positive lymph node metastasis was established based on a receiver operating characteristic (ROC) curve. A logistic model was constructed based on MRI findings and risk factors for lymph node metastasis extracted from logistic-regression analysis. The diagnostic capabilities of MRI alone and those of the logistic model were compared using the area under the curve (AUC) of the ROC curve. Results: The cut-off value was a diameter of 5.47 mm. Diagnosis using MRI had an accuracy of 65.9%, sensitivity 73.5%, specificity 61.3%, positive predictive value (PPV) 62.9%, and negative predictive value (NPV) 72.2% [AUC: 0.6739 (95%CI: 0.6016-0.7388)]. Age (<59) (p=0.0163), pT (T3+T4) (p=0.0001), and BMI (<23.5) (p=0.0003) were extracted as independent risk factors for lymph node metastasis. Diagnosis using MRI with the logistic model had an accuracy of 75.0%, sensitivity 72.3%, specificity 77.4%, PPV 74.1%, and NPV 75.8% [AUC: 0.7853 (95%CI: 0.7098-0.8454)], showing a significantly improved diagnostic capacity using the logistic model (p=0.0002). Conclusions: A logistic model including risk factors for lymph node metastasis can improve the accuracy of MRI diagnosis of rectal cancer.

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

• 상하수도학회지
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• 제34권4호
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• pp.277-288
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• 2020

In this study, we performed algorithms to predict algae of Chlorophyll-a (Chl-a). Water quality and quantity data of the middle Nakdong River area were used. At first, the correlation analysis between Chl-a and water quality and quantity data was studied. We extracted ten factors of high importance for water quality and quantity data about the two weirs. Algorithms predicted how ten factors affected Chl-a occurrence. We performed algorithms about decision tree, random forest, elastic net, gradient boosting with Python. The root mean square error (RMSE) value was used to evaluate excellent algorithms. The gradient boosting showed 10.55 of RMSE value for the Gangjeonggoryeong (GG) site and 11.43 of RMSE value for the Dalsung (DS) site. The gradient boosting algorithm showed excellent results for GG and DS sites. Prediction value for the four algorithms was also evaluated through the Receiver operating characteristic (ROC) curve and Area under curve (AUC). As a result of the evaluation, the AUC value was 0.877 at GG site and the AUC value was 0.951 at DS site. So the algorithm's ability to interpret seemed to be excellent.

• 대한물리의학회지
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• 제12권2호
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• pp.129-136
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• 2017

PURPOSE: The purpose of this study was to compare the gait of elderly patients with and without dementia to investigate the possibility of an ambulation assessment test as a diagnostic tool for dementia. METHODS: A total of 96 subjects were included with 60 participants without dementia (control group) and 36 patients with dementia (dementia group). To compare the walking ability of the two groups, a 4-m walking test (4MWT) and Groningen Meander Walking Test (GMWT) were conducted. The GMWT is graded by amount of time in seconds and by number of oversteps outside the track. Mann-Whitney U test was used to compare the gait between the groups and the area under the curve (AUC) with Received Operating Characteristic (ROC) curve was analyzed. Statistical significance was considered at a p<.05, with a 95% confidence interval. RESULTS: There were statistically significant differences (p<.05) between the dementia group and the control group for the 4MWT, GMWTSEC, and GMWTSTEP scores. The AUC was .95 for 4MWT, .92 for GMWTSEC, and .96 for GMWTSTEP with the 95% confidence interval. The cut-off values of the ROC curve were 1.03m/s for 4MWT, 10.8 second for GMWTSEC, and 3.75 steps for GMSTEP. CONCLUSION: In our study, we investigated the utility of ambulatory assessment tools to predict dementia. The results of this study suggest that the 4MWT and the GMWT used in this study are appropriate assessment tools for dementia prediction.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제29권3호
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• pp.129-136
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• 2018

Objectives: This study aimed to evaluate the efficacy of the attention-deficit/hyperactivity disorder (ADHD)-After School Checklist (ASK) by comparing the results of the Comprehensive Attention Test (CAT) and Clinical Global Impression-Severity (CGI-S) Scale and then by calculating the area under the receiver operating characteristic (ROC) curve. Methods: We performed correlation analyses on the ASK and CAT results and then the ASK and CGI-S results. We created a ROC curve and evaluated performance on the ASK as a diagnostic tool. We then analyzed the test results of 1348 subjects (male 56.8%), including 1201 subjects in the general population and 147 ADHD subjects, aged 6-15 years, from kindergarten to middle school in Seoul and Gyeonggi province, South Korea. Results: According to the correlation analyses, ASK scores and the Attention Quotient (AQ) of CAT scores showed a significant correlation of -0.20--0.29 (p<0.05). The t-test between ADHD scores and CGI-S also showed a significant correlation (t=-2.55, p<0.05). The area under the ROC curve was calculated as 0.81, indicating good efficacy of the ASK, and the cut-off score was calculated as 15.5. Conclusion: The ASK can be used as a valid tool not only to evaluate functional impairment of ADHD children and adolescents but also to screen ADHD.

• Genomics & Informatics
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• 제16권4호
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• pp.26.1-26.12
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• 2018

Shigella spp. constitutes some of the key pathogens responsible for the global burden of diarrhoeal disease. With over 164 million reported cases per annum, shigellosis accounts for 1.1 million deaths each year. Majority of these cases occur among the children of the developing nations and the emergence of multi-drug resistance Shigella strains in clinical isolates demands the development of better/new drugs against this pathogen. The genome of Shigella flexneri was extensively analyzed and found 4,362 proteins among which the functions of 674 proteins, termed as hypothetical proteins (HPs) had not been previously elucidated. Amino acid sequences of all these 674 HPs were studied and the functions of a total of 39 HPs have been assigned with high level of confidence. Here we have utilized a combination of the latest versions of databases to assign the precise function of HPs for which no experimental information is available. These HPs were found to belong to various classes of proteins such as enzymes, binding proteins, signal transducers, lipoprotein, transporters, virulence and other proteins. Evaluation of the performance of the various computational tools conducted using receiver operating characteristic curve analysis and a resoundingly high average accuracy of 93.6% were obtained. Our comprehensive analysis will help to gain greater understanding for the development of many novel potential therapeutic interventions to defeat Shigella infection.