• Proceedings of the Korean Society of Embryo Transfer Conference
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• 2003.10a
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• pp.103-103
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• 2003

• 대한핵의학회:학술대회논문집
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• 2006.05a
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• pp.51-52
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• 2006

• Journal of Digital Convergence
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• v.16 no.9
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• pp.279-291
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• 2018

This study is designed to demonstrate risk factors of unmet medical care for people with cerebrovascular disease. To do this, statistical analysis was performed by using hierarchical logistic regression analysis with SPSS/WIN24.0 program using Korean Medical Panel data in 2014. In the final model of the hierarchical logistic regression analysis, which is based on Anderson's Model, adjusted for the factors of the predisposing and enabling factors, the explanatory variables affecting the unmet medical development are gender, economic activity, income level, the experience of lying in a sickbed, restriction on activity, subjective health condition, and the number of chronic diseases. Based on the results of this study, the practical and policy implications for the effective management and treatment of cerebrovascular disease should be included in the countermeasures for cerebrovascular disease, a strategy to reduce the unmet medical incidence of cerebrovascular disease, in order to meet the medical needs, the necessity of comprehensive measures considering various dimensions of variables and the influential variables of unmet medical emergence have been suggested for the necessity of making a detailed service manual that can improve accessibility to medical services.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.6 no.1
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• pp.88-96
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• 1996

This study was conducted to establish model between lead and ZPP concentration in blood of workers exposed to lead. Workers employed in secondary smelting manufacturing industry showed $85.1{\mu}g/dl$ of blood lead level, exceeding $60{\mu}g/dl$, the Criteria for Removal defined by Occupational Safety and Health Act of Korea. Average blood lead level of workers in the battery manufacturing industry was $51.3{\mu}g/dl$, locating between $40{\mu}g/dl$ and $60{\mu}g/dl$, the Criteria for Requiring Medical Removal. Blood lead level of in the litharge and radiator manufacturing industry was below $40{\mu}g/dl$, the Criteria Requiring Temporary Medical Removal. Blood lead levels of workers by industry were Significantly different(p<0.05). 50(21 %) showed blood lead levels above $60{\mu}g/dl$, the Criteria for Removal and 66(27.7 %) showed blood lead levels between the Criteria for Requiring Medical Removal, $40-60{\mu}g/dl$. Thus, approximately 50 percent of workers indicated blood lead levels above $40{\mu}g/dl$, the Criteria Requiring Temporary Medical Removal and should receive medical examination and consultation including biological monitoring. Average ZPP level of workers employed in the secondary smelting industry was $186.2{\mu}g/dl$, exceeding above $150{\mu}g/dl$, the Criteria for Removal. Seventy seven of all workers(32.3 %) showed ZPP level above $100-150{\mu}g/dl$, the Criteria for Requiring Medical Removal. The most appropriate model for predicting ZPP in blood was log-linear regression model. Log linear regression models between lead and ZPP concentrations in blood was Log ZPP(${\mu}g/dl$) = -0.2340 + 1.2270 Log Pb-B(${\mu}g/dl$)(standard error of estimate: 0,089, ${\gamma}^2=0.4456$, n=238, P=0.0001), Blood-in-lead explained 44.56 % of the variance in log(ZPP in blood).

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5621-5626
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• 2014

N-acetyltransferase 2 (NAT2) is a polymorphic enzyme that plays an important role in the metabolism of various potential carcinogens. In recent years, a number of studies have been carried out to investigate the relationship between the rs1799930 and rs1799931 polymorphism in NAT2 and cancer risk in multiple populations for different types of cancer. However, the results were not consistent. Therefore, we performed a meta-analysis to further explore the relationship between NAT2 polymorphism and the risk of cancer. A total of 21 studies involving 15, 450 subjects for rs1799930 and 13, 011 subjects for rs1799931 were included in this meta-analysis. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess strength of associations. We also evaluated the publication bias and performed a sensitivity analysis. Overall, our results showed an apparent significant association between the NAT2 rs1799930 polymorphism and cancer susceptibility in Asians (GA vs. GG: OR=1.22, 95% CI=1.03-1.45; dominant model: OR=1.22, 95% CI=1.03-1.43) and population-based controls (GA vs. GG: OR=1.10, 95% CI=1.01-1.19; dominant model: OR=1.09, 95% CI=1.01-1.18). In contrast, a significant association was observed between the NAT2 rs1799931 G>A polymorphism and decreased cancer susceptibility in overall meta-analysis (AA vs. GG: OR=0.55, 95% CI=0.33-0.93; GA vs. GG: OR=1.00, 95% CI=0.88-1.14; dominant model: OR=0.97, 95% CI=0.86-1.10; recessive model: OR=0.56, 95% CI=0.34-0.94) and the Asian group (AA vs. GG: OR=0.50, 95% CI=0.26-0.94; recessive model, OR=0.50, 95% CI=0.27-0.94). We found that the NAT2 rs1799930 may be a risk factor, while the NAT2 rs1799931 polymorphism is associated with a decreased risk of cancer and is likely a protective factor against cancer development.

• Korean Journal of Radiology
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• v.25 no.2
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• pp.189-198
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• 2024

Objective: To investigate the prognostic utility of radiomics features extracted from ¹⁸F-fluorodeoxyglucose (FDG) PET/CT combined with clinical factors and metabolic parameters in predicting progression-free survival (PFS) and overall survival (OS) in individuals diagnosed with extranodal nasal-type NK/T cell lymphoma (ENKTCL). Materials and Methods: A total of 126 adults with ENKTCL who underwent ¹⁸F-FDG PET/CT examination before treatment were retrospectively included and randomly divided into training (n = 88) and validation cohorts (n = 38) at a ratio of 7:3. Least absolute shrinkage and selection operation Cox regression analysis was used to select the best radiomics features and calculate each patient's radiomics scores (RadPFS and RadOS). Kaplan-Meier curve and Log-rank test were used to compare survival between patient groups risk-stratified by the radiomics scores. Various models to predict PFS and OS were constructed, including clinical, metabolic, clinical + metabolic, and clinical + metabolic + radiomics models. The discriminative ability of each model was evaluated using Harrell's C index. The performance of each model in predicting PFS and OS for 1-, 3-, and 5-years was evaluated using the time-dependent receiver operating characteristic (ROC) curve. Results: Kaplan-Meier curve analysis demonstrated that the radiomics scores effectively identified high- and low-risk patients (all P < 0.05). Multivariable Cox analysis showed that the Ann Arbor stage, maximum standardized uptake value (SUVmax), and RadPFS were independent risk factors associated with PFS. Further, β2-microglobulin, Eastern Cooperative Oncology Group performance status score, SUVmax, and RadOS were independent risk factors for OS. The clinical + metabolic + radiomics model exhibited the greatest discriminative ability for both PFS (Harrell's C-index: 0.805 in the validation cohort) and OS (Harrell's C-index: 0.833 in the validation cohort). The time-dependent ROC analysis indicated that the clinical + metabolic + radiomics model had the best predictive performance. Conclusion: The PET/CT-based clinical + metabolic + radiomics model can enhance prognostication among patients with ENKTCL and may be a non-invasive and efficient risk stratification tool for clinical practice.

• The Journal of Korean Medicine
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• v.37 no.1
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• pp.101-113
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• 2016

Objectives: The purpose of this study was to develop a competency model for the Korean medicine doctors and find application plans for the future education in Korean medicine. Methods: Based on literature review, we drafted a competency model framework for modeling and defined competencies using generic model overlay method. Also we conducted a FGI with 20 extension specialists in Korean medicine to validate competency model. Results: Findings are 5 domains and 15 competencies. 5 domains have optimal patient care, reasonable communication skill, professionalism enhancement, performing social accountability, and efficient clinical management. 3 competencies are included in 5 domains each. With this model, 4 ways of application plans are shown to apply for the future competency-based education in Korean medicine. Conclusion: Developed 2016 competency model for the Korean medicine doctors can be a first huge step to innovate education in Korean medicine toward competency-based educational system.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.369-375
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• 2001

The statistical regression model is one of the most frequently used clinical analysis methods. It has basic assumption of linearity, additivity and normal distribution of data. However, most of biological data in medical field are nonlinear and unevenly distributed. To overcome the discrepancy between the basic assumption of statistical model and actual biological data, we propose a new analytical method based on artificial neural network. The newly developed multilayer perceptron(MLP) is trained with 120 data set (60 normal, 60 patient). On applying test data, it shows the discrimination power of 0.76. The diabetic risk factors were also identified from the MLP neural network model and the logistic regression model. The signigicant risk factors identified by MLP model were post prandial glucose level(PP2), sex(male), fasting blood sugar(FBS) level, age, SBP, AC and WHR. Those from the regression model are sex(male), PP2, age and FBS. The combined risk factors can be identified using the MLP model. Those are total cholesterol and body weight, which is consistent with the result of other clinical studies. From this experiment we have learned that MLP can be applied to the combined risk factor analysis of biological data which can not be provided by the conventional statistical method.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6709-6714
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• 2014

The rs2273535 polymorphism in the AURKA gene had proven to be associated with breast carcinoma susceptibility. Nevertheless, the results of different studies remain contradictory. A meta-analysis covering 28, 789 subjects from eleven different studies was here carried out in order to investigate the association in detail. The random effects model was used to analyze the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs). A significant relationship between the rs2273535 polymorphism and breast tumors was found in an allelic genetic model (OR: 1.076, 95% CI: 1.004-1.153, p=0.040, $P_{heterogeneity}$=0.002). No significant association was detected in a homozygote model (OR: 1.186, 95% CI: 0.990-1.423, P=0.065, $P_{heterogeneity}$=0.002), a heterozygote model (OR: 1.016, 95% CI: 0.959-1.076, p=0.064, $P_{heterogeneity}$=0.000), a dominant genetic model (OR: 1.147, 95% CI: 0.992-1.325, p=0.217, $P_{heterogeneity}$=0.294) and a recessive genetic model (OR: 1.093, 95% CI: 0.878-1.361, p=0.425, $P_{heterogeneity}$=0.707). A significant relationship between the rs2273535 polymorphism in the AURKA gene and breast tumor in Asian group was found in an allelic genetic model (OR: 1.124, 95% CI: 1.003-1.29, p=0.044, $P_{heterogeneity}$=0.034), a homozygote model (OR: 1.229, 95% CI: 1.038-1.455, p=0.016, $P_{heterogeneity}$=0.266) and a recessive genetic model (OR: 1.227, 95% CI: 1.001-1.504, p=0.049, $P_{heterogeneity}$=0.006). A significant association was thus observed between the rs2273535 polymorphism in the AURKA gene and breast cancer risk. Individuals with the rs2273535 polymorphism in the AURKA gene have a higher risk of breast cancer in Asian populations, but not in Caucasians.

• Journal of The Korean Radiological Technologist Association
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• v.25 no.1
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• pp.92-93
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• 1999