• Title/Summary/Keyword: predictive tool

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Comparison of Vessel Disease and Gensini Score according to Ankle-Brachial Index in Patients with Cardiovascular Disease (심혈관 질환자의 발목-상완 지수에 따른 Vessel disease 및 Gensini score 비교 융복합 연구)

  • Choi, Suk-Kyeong;Choi, Hye-Ran
    • Journal of Digital Convergence
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    • v.15 no.1
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    • pp.267-275
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    • 2017
  • The purpose of this study was to evaluate the clinical availability of ankle-brachial index(ABI) according to severity of cardiovascular disease. The subjects of this study were the patients who had ABI in a general hospital. In this study, total 441 patients were enrolled for analysis. Electric medical records were reviewed to investigate the result of ABI and severity of cardiovascular disease measured vessel disease and Gensini score. Collected data were analyzed using SPSS 21.0 program. Subjects with $ABI{\leq}0.90$ and > 0.90 were classified as having abnormal and normal ABI. There were significant differences in vessel disease categorization($x^2=4.731$, p=.030) and Gensini score(t=2.351, p=.019) between two groups. Therefore, ABI is an effective and non-invasive tool for the diagnosis of cardiovascular disease with high severity. ABI is a valuable predictive index of ischemic heart disease.

A Study about Internal Control Deficient Company Forecasting and Characteristics - Based on listed and unlisted companies - (내부통제 취약기업 예측과 특성에 관한 연구 - 상장기업군과 비상장기업군 중심으로 -)

  • Yoo, Kil-Hyun;Kim, Dae-Lyong
    • Journal of Digital Convergence
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    • v.15 no.2
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    • pp.121-133
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    • 2017
  • The propose of study is to examine the characteristics of companies with high possibility to form an internal control weakness using forecasting model. This study use the actual listed/unlisted companies' data from K_financial institution. The first conclusion is that discriminant model is more valid than logit model to predict internal control weak companies. A discriminant model for predicting the vulnerability of internal control has high classification accuracy and has low the Type II error that is incorrectly classifying vulnerable companies to normal companies. The second conclusion is that the characteristic of weak internal control companies have a low credit rating, low asset soundness assessment, high delinquency rates, lower operating cash flow, high debt ratios, and minus operating profit to the net sales ratio. As not only a case of listed companies but unlisted companies which did not occur in previous studies are extended in this study, research results including the forecasting model can be used as a predictive tool of financial institutions predicting companies with high potential internal control weakness to prevent asset losses.

A Study on the Value Factors of Culture Consumers for Corporate Culture Marketing through Big Data Techniques (빅데이터 기법을 통한 기업 문화마케팅을 위한 문화소비자의 가치 요소 연구)

  • Oh, Se Jong
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.1
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    • pp.31-36
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    • 2020
  • Corporate Culture Marketing is a marketing tool that enhances a company's cultural image or conveys its image through culture. Culture Consumer value analysis is important predictive data in identifying the value and pursuit of life in individual consumption behavior, explaining the choice behavior of culture consumers, and serves as the basis for decision making. The research method was linked to the text mining and opinion mining techniques of big data, and extracted positive, negative and neutral words. The analysis targets culture consumers participating in concerts at Hyundai Card's 'Super Concert', which is subject to domestic consumers, and CJ ENM's 'KCON', which is subject to foreign consumers. The culture consumer value elements of corporate culture marketing are the basic conditions, and they were derived as 'Consensus Communication (Expression of Sensibility)', 'Participation Sharing(VIP Belonging)', 'Social Change Issue', 'Differentiating Services', 'Price Discount Benefit' and 'Location Quality'. In the future, we will need to foster 'Culture Technology Marketers' and apply them in areas such as arts management planning, cultural investment, cultural distribution, cultural space, Corporate Culture, CSR and K-pop marketing to enhance corporate interests and brand value and enhance brand value.

Development of the EMC-based Empirical Model for Estimating Pollutant Loads from Small Agricultural Watersheds (농촌 소유역에서 EMC를 이용한 오염물질 부하량 산정기법의 개발)

  • Kim, Young-Chul;Kim, Geon-Ha;Lee, Dong-Ryul
    • Journal of Korea Water Resources Association
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    • v.36 no.4
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    • pp.691-703
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    • 2003
  • In this paper, a new and integrated approach easily used to calculate the pollutant loads from agricultural watersheds is suggested. Basic concepts of this empirical tool are based on the hypotheses that variations in event mean concentrations(EMCs) of the pollutants from a given agricultural watershed during rainstorms are only due to the rainfall pattern. This assumption would be feasible to agricultural watersheds whose land uses does not change during the cultivation period overlapped by rainy season and also in which point-sources of the pollutants are rare. Therefore, if EMC data sets through extensive sampling from various rural areas are available, it is possible to establish relationships between EMCs, shapes and land uses of the watersheds, and rainfall events. For this purpose, fifty one sets of EMC values were obtained from nine different watersheds, and those data were used to develop predictive tools for the EMCs of 55, COD, TN and TP in rainfall runoff. The results of the statistical tests for those formulas show that they are not only fairly good in predicting actual EMC values of some parameters, but also useful in terms of calculating pollutant loads on any time-spans such as the day of rainfall event or weekly, monthly, and yearly. Their applicability was briefly demonstrated and discussed. Also, the unit loads calculated from EMCs based on different land uses and real rainfall data over one of the watershed used for this study. were provided, and they are compared with other well-known unit loads.

A study on the development of severity-adjusted mortality prediction model for discharged patient with acute stroke using machine learning (머신러닝을 이용한 급성 뇌졸중 퇴원 환자의 중증도 보정 사망 예측 모형 개발에 관한 연구)

  • Baek, Seol-Kyung;Park, Jong-Ho;Kang, Sung-Hong;Park, Hye-Jin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.126-136
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    • 2018
  • The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

QTc Prolongation due to Psychotropic Drugs Intoxication and Its Risk Assessment (향정신성 약물 중독에 의한 QTc 연장과 그 위험성에 대한 고찰)

  • Park, Kwan Ho;Hong, Hoon Pyo;Lee, Jong Seok;Jeong, Ki Young;Ko, Seok Hun;Kim, Sung Kyu;Choi, Han Sung
    • Journal of The Korean Society of Clinical Toxicology
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    • v.18 no.2
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    • pp.66-77
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    • 2020
  • Purpose: The aims of the present study were twofold. First, the research investigated the effect of an individual's risk factors and the prevalence of psychotropic drugs on QTc prolongation, TdP (torsades de pointes), and death. Second, the study compared the risk scoring systems (the Mayo Pro-QT risk score and the Tisadale risk score) on QTc prolongation. Methods: The medical records of intoxicated patients who visited the emergency department between March 2010 and February 2019 were reviewed retrospectively. Among 733 patients, the present study included 426 psychotropic drug-intoxicated patients. The patients were categorized according to the QTc value. The known risk factors of QTc prolongation were examined, and the Mayo Pro-QT risk score and the Tisadale risk score were calculated. The analysis was performed using multiple logistic regression, Spearman correlation, and ROC (receiver operating characteristic). Results: The numbers in the mild to moderate group (male: 470≤QTc<500 ms, female: 480≤QTc<500 ms) and severe group (QTc≥500 ms or increase of QTc at least 60ms from baseline, both sex) were 68 and 95, respectively. TdP did not occur, and the only cause of death was aspiration pneumonia. The statically significant risk factors were multidrug intoxications of TCA (tricyclic antidepressant), atypical antipsychotics, an atypical antidepressant, panic disorder, and hypokalemia. The Tisadale risk score was larger than the Mayo Pro-QT risk score. Conclusion: Multiple psychotropic drugs intoxication (TCA, an atypical antidepressant, and atypical antipsychotics), panic disorder, and hypokalemia have been proven to be the main risk factors of QTc prolongation, which require enhanced attention. The present study showed that the Tisadale score had a stronger correlation and predictive accuracy for QTc prolongation than the Mayo Pro-QT score. As a result, the Tisadale risk score is a crucial assessment tool for psychotropic drug-intoxicated patients in a clinical setting.

Development and Validation of the Vicarious Trauma Scale for Sexual Violence Counselor (성폭력 상담자 대리외상 척도 개발 및 타당화)

  • Heo, Chan-hee;Lee, Jee-yon
    • The Journal of the Korea Contents Association
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    • v.20 no.12
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    • pp.393-405
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    • 2020
  • The purpose of this study is to develop and validate a scale of vicarious trauma for sexual violence counselors. To this end, the concept of composition and preliminary questions of the vicarious trauma of sexual violence counselors were selected through the analysis of a content of individual interviews of sexual violence counselors and the precedent theory. Then, preliminary scale was developed after expert's evaluation of the validity of the contents. Next, as a result of a confirmatory factor analysis on the preliminary scale of 349 sexual violence counselors with experience in consulting sexual violence clients, it is confirmed that the conformity of five-factor structure was found to be favorable. As a result of convergent and discriminative validity analysis, it was confirmed that the developed scale is a reasonable tool for measuring vicarious trauma of sexual violence counselors by showing proper correlation with Secondary Traumatic Stress Scale, Counselor Burnout Inventory and Inventory of Countertransference Behavior. Furthermore, as a result of correlation analysis between professional identity and Belief in a Just World, it confirmed that it has predictive validity of the scale by indicating a high negative correlation. Furthermore, the relationship between the scale of vicarious trauma of sexual violence counselors and career background was analyzed. Finally, based on the results of this study, the significance and limitations of this study and the direction of future research were discussed.

A Study on Optimized Artificial Neural Network Model for the Prediction of Bearing Capacity of Driven Piles (항타말뚝의 지지력 예측을 위한 최적의 인공신경망모델에 관한 연구)

  • Park Hyun-Il;Seok Jeong-Woo;Hwang Dae-Jin;Cho Chun-Whan
    • Journal of the Korean Geotechnical Society
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    • v.22 no.6
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    • pp.15-26
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    • 2006
  • Although numerous investigations have been performed over the years to predict the behavior and bearing capacity of piles, the mechanisms are not yet entirely understood. The prediction of bearing capacity is a difficult task, because large numbers of factors affect the capacity and also have complex relationship one another. Therefore, it is extremely difficult to search the essential factors among many factors, which are related with ground condition, pile type, driving condition and others, and then appropriately consider complicated relationship among the searched factors. The present paper describes the application of Artificial Neural Network (ANN) in predicting the capacity including its components at the tip and along the shaft from dynamic load test of the driven piles. Firstly, the effect of each factor on the value of bearing capacity is investigated on the basis of sensitivity analysis using ANN modeling. Secondly, the authors use the design methodology composed of ANN and genetic algorithm (GA) to find optimal neural network model to predict the bearing capacity. The authors allow this methodology to find the appropriate combination of input parameters, the number of hidden units and the transfer structure among the input, the hidden and the out layers. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the bearing capacity of driven piles.

Neutrophil to Lymphocyte Ratio and Serum Biomarkers : A Potential Tool for Prediction of Clinically Relevant Cerebral Vasospasm after Aneurysmal Subarachnoid Hemorrhage

  • Osman Kula;Burak Gunay;Merve Yaren Kayabas;Yener Akturk;Ezgi Kula;Banu Tutunculer;Necdet Sut;Serdar Solak
    • Journal of Korean Neurosurgical Society
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    • v.66 no.6
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    • pp.681-689
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    • 2023
  • Objective : Subarachnoid hemorrhage (SAH) is a condition characterized by bleeding in the subarachnoid space, often resulting from the rupture of a cerebral aneurysm. Delayed cerebral ischemia caused by vasospasm is a significant cause of mortality and morbidity in SAH patients, and inflammatory markers such as systemic inflammatory response index (SIRI), systemic inflammatory index (SII), neutrophil-to-lymphocyte ratio (NLR), and derived NLR (dNLR) have shown potential in predicting clinical vasospasm and outcomes in SAH patients. This article aims to investigate the relationship between inflammatory markers and cerebral vasospasm after aneurysmatic SAH (aSAH) and evaluate the predictive value of various indices, including SIRI, SII, NLR, and dNLR, in predicting clinical vasospasm. Methods : A retrospective analysis was performed on a cohort of 96 patients who met the inclusion criteria out of a total of 139 patients admitted Trakya University Hospital with a confirmed diagnosis of aSAH between January 2013 and December 2021. Diagnostic procedures, neurological examinations, and laboratory tests were performed to assess the patients' condition. The Student's t-test compared age variables, while the chi-square test compared categorical variables between the non-vasospasm (NVS) and vasospasm (VS) groups. Receiver operating characteristic (ROC) curve analyses were used to evaluate the diagnostic accuracy of laboratory parameters, calculating the area under the ROC curve, cut-off values, sensitivity, and specificity. A significance level of p<0.05 was considered statistically significant. Results : The study included 96 patients divided into two groups : NVS and VS. Various laboratory parameters, such as NLR, SII, and dNLR, were measured daily for 15 days, and statistically significant differences were found in NLR on 7 days, with specific cut-off values identified for each day. SII showed a significant difference on day 9, while dNLR had significant differences on days 2, 4, and 9. Graphs depicting the values of these markers for each day are provided. Conclusion : Neuroinflammatory biomarkers, when used alongside radiology and scoring scales, can aid in predicting prognosis, determining severity and treatment decisions for aSAH, and further studies with larger patient groups are needed to gain more insights.

Two-Dimensional Shear Wave Elastography Predicts Liver Fibrosis in Jaundiced Infants with Suspected Biliary Atresia: A Prospective Study

  • Huadong Chen;Luyao Zhou;Bing Liao;Qinghua Cao;Hong Jiang;Wenying Zhou;Guotao Wang;Xiaoyan Xie
    • Korean Journal of Radiology
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    • v.22 no.6
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    • pp.959-969
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    • 2021
  • Objective: This study aimed to evaluate the role of preoperative two-dimensional (2D) shear wave elastography (SWE) in assessing the stages of liver fibrosis in patients with suspected biliary atresia (BA) and compared its diagnostic performance with those of serum fibrosis biomarkers. Materials and Methods: This study was approved by the ethical committee, and written informed parental consent was obtained. Two hundred and sixteen patients were prospectively enrolled between January 2012 and October 2018. The 2D SWE measurements of 69 patients have been previously reported. 2D SWE measurements, serum fibrosis biomarkers, including fibrotic markers and biochemical test results, and liver histology parameters were obtained. 2D SWE values, serum biomarkers including, aspartate aminotransferase to platelet ratio index (APRi), and other serum fibrotic markers were correlated with the stages of liver fibrosis by METAVIR. Receiver operating characteristic (ROC) curves and area under the ROC (AUROC) curve analyses were used. Results: The correlation coefficient of 2D SWE value in correlation with the stages of liver fibrosis was 0.789 (p < 0.001). The cut-off values of 2D SWE were calculated as 9.1 kPa for F1, 11.6 kPa for F2, 13.0 kPa for F3, and 15.7 kPa for F4. The AUROCs of 2D SWE in the determination of the stages of liver fibrosis ranged from 0.869 to 0.941. The sensitivity and negative predictive value of 2D SWE in the diagnosis of ≥ F3 was 93.4% and 96.0%, respectively. The diagnostic performance of 2D SWE was superior to that of APRi and other serum fibrotic markers in predicting severe fibrosis and cirrhosis (all p < 0.005) and other serum biomarkers. Multivariate analysis showed that the 2D SWE value was the only statistically significant parameter for predicting liver fibrosis. Conclusion: 2D SWE is a more effective non-invasive tool for predicting the stage of liver fibrosis in patients with suspected BA, compared with serum fibrosis biomarkers.