• Journal of Chest Surgery
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• v.57 no.1
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• pp.44-52
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• 2024

Background: Visceral pleural invasion (VPI) is a poor prognostic factor that contributes to the upstaging of early lung cancers. However, the preoperative assessment of VPI presents challenges. This study was conducted to examine intraoperative pleural carcinoembryonic antigen (pCEA) level and maximum standardized uptake value (SUVmax) as predictive markers of VPI in patients with clinical T1N0M0 lung adenocarcinoma. Methods: A retrospective review was conducted of the medical records of 613 patients who underwent intraoperative pCEA sampling and lung resection for non-small cell lung cancer. Of these, 390 individuals with clinical stage I adenocarcinoma and tumors ≤30 mm were included. Based on computed tomography findings, these patients were divided into pleural contact (n=186) and non-pleural contact (n=204) groups. A receiver operating characteristic (ROC) curve was constructed to analyze the association between pCEA and SUVmax in relation to VPI. Additionally, logistic regression analysis was performed to evaluate risk factors for VPI in each group. Results: ROC curve analysis revealed that pCEA level greater than 2.565 ng/mL (area under the curve [AUC]=0.751) and SUVmax above 4.25 (AUC=0.801) were highly predictive of VPI in patients exhibiting pleural contact. Based on multivariable analysis, pCEA (odds ratio [OR], 3.00; 95% confidence interval [CI], 1.14-7.87; p=0.026) and SUVmax (OR, 5.25; 95% CI, 1.90-14.50; p=0.001) were significant risk factors for VPI in the pleural contact group. Conclusion: In patients with clinical stage I lung adenocarcinoma exhibiting pleural contact, pCEA and SUVmax are potential predictive indicators of VPI. These markers may be helpful in planning for lung cancer surgery.

• Journal of Animal Science and Technology
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• v.48 no.2
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• pp.151-160
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• 2006

This study was conducted to investigate the genetic characteristics of growth stages in Hanwoo, to provide useful information in farm management decisions. Data were taken from the nucleus herds of three farms, Namwon, Daegwalyong and Seosan, comprising 27,647 cows, 14,744 bulls, and 1,290 steers in between 1980 and 2004. According to the growth curve by year, the residuals for cows and bulls were 68.49 and 54.29, respectively, under the Gompertz model. The values were lower than in other years. Parameters, A, b and k were estimated as 423.6±5.8, 2.387±0.064 and 0.0908±0.0033 in cows and 823.3±15.3, 3.584±0.070, 0.1139±0.0032 in bulls, respectively. The fitness was higher under the Gompertz model than under the logistic model: monthly and daily estimation for cows were 379.3±7.509, 2.499±0.057, 0.114±0.0045 and 367.1±1.9003, 2.3983±0.012, 0.004±0.00003, respectively. Estimated residual mean squares were 31.85 and 998.4 in their respective models. Monthly and daily estimation of bulls were 834.6±22.00, 3.319±0.062, 0.104±0.0037 and 796.0±6.128, 3.184±0.014, 0.003±0.00003, respectively. Estimated residual mean square were 66.18 and 2106.5. Monthly and daily estimation of steers were 1049.1±144.2, 3.024±0.008, 0.067±0.0096 and 1505.1±176.6, 2.997±0.067, 0.001±0.0001, relatively. Squares, 186.0 and 1119.1. In terms of growth characteristic estimated by Gompertz model, body weight for cows and bulls were 139.53kg and 307.03kg, and the daily gains were 0.52kg and 1.04kg, respectively. Body weight for steers was 385.94kg at the inflection point. Body weight gain was 0.84kg in both models. Our results showed that cows had lower mature weight and daily weight gain, and reached the inflection point earlier than bulls or steers.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.29 no.4
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• pp.247-259
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• 1993

The fishing experiment was carried out by the training ship Saebada in order to analyse the mesh selectivity for trawl cod-end, in the Southern Korea Sea and the East China Sea from June. 1991 through August, 1992. The trawl cod-end used in this experiment has the trouser type of cod-end with cover net. and the mesh selectivity was examined for the five kinds of the opening of mesh in its cod-end part. A total of 163 hauls, of which having mesh size 51.2mm ; A 89, 70.2mm ; B 54, 77.6mm ; C 55, 88.0mm ; D 52 and 111.3mm ; E 20 were used respectively. Selection curves and selection parameters were calculated by using a logistic function, S=1/(1+exp super(-(aL+b)) ). The mesh election master curves were estimated by S=1/(1+exp super(-[a(L/M)+$\beta$]) ). and the optimum mesh size were calculated with (L/M) sub(50) of master curve. In these cases 'a' and '$\alpha$' are slope, 'b' and '$\beta$' are intercept. 'L' is body length of the target species of fishes, 'M' is the mesh size, and 'S' denotes mesh selectivity. In this report, the four species of compressed form fishes were taken analized according to fish shape, and 'S' denotes mesh selectivity. In this report, the four species of compressed form fishes were taken analized according to fish shape, and the results obtained are summarized as follows: 1. Red seabream Pagrus major(Temminct et Schlegel) and yellow porgy Dentex tumifrons(Temminct et Schlegel) ; Selection rate in each mesh size of A, B, C, D and E were 99.7%, 97.5%, 91.4%, 76.7% and 57.8% respectively. Selection parameters 'a' and 'b' of mesh sizes C, D and E were 2.65 and -28.62, 4.40 and -77.73, 2.31 and -46.99, and their selection factors were 1.39, 2.10, 1.83 respectively. Selection parameters of master curve '$\alpha$' and '$\beta$' were 3.05 and -5.65 respectively, and (L/M) sub(50) was 1.85. The optimum mesh size of Red seabream was 141mm. 2. Filefish Thamnaconus modestus (Gunther) ; Selection rate in each mesh size of A, B, C, D and E were 99.6%, 98.3%, 91.2%, 80.0% and 48.6% respectively. Selection parameters 'a' and 'b' of mesh sizes C, D and E were 5.82 and -55.10, 2.92 and -36.90, 3.91 and -63.09, and their selection factors were 1.35, 1.44, 1.45 respectively. Selection parameters of master curve '$\alpha$' and '$\beta$' were 3.02 and -4.32 respectively, and (L/M) sub(50) was 1.43. The optimum mesh size was 129mm. 3. Target dory Zeus faber Valenciennes ; Selection rate in each mesh size of A, B, C, D and E were 99.7%, 100%, 83.2%, 91.6% and 65.0% respectively. Selection parameters 'a' and 'b' of mesh sizes C, D and E were 3.85 and -32.46, 4.19 and -57.38, 2.45 and -40.03, and their selection factors were 1.09, 1.56, 1.47 respectively. Selection parameters of master curve '$\alpha$' and '$\beta$' were 2.64 and -3.53 respectively, and (L/M) sub(50) was 1.34. The optimum mesh size was 127mm. 4. Butterfish Psenopsis anomala (Temminct et Schlegel) ; Selection rate in each mesh size of A, B, C, D and E were 99.2%, 34.1%, 46.5%, 14.3% and 2.4% respectively. Selection parameters 'a' and 'b' of mesh sizes B, C and D were 5.35 and -71.70, 5.07 and -69.25, 3.31 and -62.06 and their selection factors were 1.91, 1.75, 2.13 respectively. Selection parameters of master curve '$\alpha$' and '$\beta$' were 3.16 and -6.24 respectively, and (L/M) sub(50) was 1.98. The optimum mesh size was 71mm.

• Clinical and Experimental Reproductive Medicine
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• v.42 no.4
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• pp.143-148
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• 2015

Objective: The aim of the current study was to determine the predictive value of anti-$M{\ddot{u}}llerian$ hormone (AMH) levels for pregnancy outcomes in patients over 40 years of age who underwent in vitro fertilization or intracytoplasmic sperm injection-embryo transfer (IVF/ICSI-ET) cycles. Methods: We retrospectively analyzed the medical records of 188 women aged 40 to 44 years who underwent IVF/ICSI-fresh ET cycles due to unexplained infertility in the fertility center of CHA Gangnam Medical Center. Patients were divided into group A, with AMH levels <1.0 ng/mL (n=97), and group B, with AMH levels ${\geq}1.0ng/mL$ (n=91). We compared the clinical pregnancy rate (CPR) in the two groups and performed logistic regression analysis to identify factors that had a significant effect on the CPR. Results: The CPR was significantly lower in group A than group B (7.2% vs. 24.2%, p<0.001). In multivariate logistic regression analysis, AMH levels were the only factor that had a significant impact on the CPR (odds ratio, 1.510; 95% confidence interval, 1.172-1.947). The area under the receiver operating characteristic curve for AMH levels as a predictor of the CPR was 0.721. When the cut-off level of AMH was set at 1.90 ng/ mL, the CPR was 6.731-fold higher in the group with AMH levels ${\geq}1.90ng/mL$ than in the group with AMH levels <1.90 ng/mL (p<0.001). Conclusion: Our study showed that AMH levels were predictive of clinical pregnancy in infertility patients over 40 years of age. Further prospective studies should be conducted to validate the predictive capability of AMH levels for the outcome of clinical pregnancy.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1185-1193
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• 2021

Objective: Clear cell sarcoma of the kidney (CCSK) is the second-most common but extremely rare primary renal malignancy in children after Wilms' tumor. The aims of this study were to evaluate the imaging features that could distinguish between CCSK and Wilms' tumor and to assess the features with diagnostic value for identifying CCSK. Materials and Methods: We reviewed the initial contrast-enhanced abdominal-pelvic CT scans of children with CCSK and Wilms' tumor between 2010 to 2019. Fifty-eight children (32 males and 26 females; age, 0.3-10 years), 7 with CCSK, and 51 with Wilms' tumor, were included. The maximum tumor diameter, presence of engorged perinephric vessels, maximum density of the tumor (Tmax) of the enhancing solid portion, paraspinal muscle, contralateral renal vein density, and density ratios (Tmax/muscle and Tmax/vein) were analyzed on the renal parenchymal phase of contrast-enhanced CT. Fisher's exact tests and Mann-Whitney U tests were conducted to analyze the categorical and continuous variables, respectively. Logistic regression and receiver operating characteristic curve analyses were also performed. Results: The age, sex, and tumor diameter did not differ between the two groups. Engorged perinephric vessels were more common in patients in the CCSK group (71% [5/7] vs. 16% [8/51], p = 0.005). Tmax (median, 148.0 vs. 111.0 Hounsfield unit, p = 0.004), Tmax/muscle (median, 2.64 vs. 1.67, p = 0.002), and Tmax/vein (median, 0.94 vs. 0.59, p = 0.002) were higher in the CCSK compared to the Wilms' group. Multiple logistic regression revealed that engorged vessels (odds ratio 13.615; 95% confidence interval [CI], 1.770-104.730) and Tmax/muscle (odds ratio 5.881; 95% CI, 1.337-25.871) were significant predictors of CCSK. The cutoff values of Tmax/muscle (86% sensitivity, 77% specificity) and Tmax/vein (71% sensitivity, 86% specificity) for the diagnosis of CCSK were 1.97 and 0.76, respectively. Conclusion: Perinephric vessel engorgement and greater tumor enhancement (Tmax/muscle > 1.97 or Tmax/vein > 0.76) are helpful for differentiating between CCSK and Wilms' tumor in children aged below 10 years.

• Journal of The Korean Society of Emergency Medicine
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• v.29 no.5
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• pp.449-454
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• 2018

Objective: The SAFARI score was introduced to assess the risk of convulsive seizure during admission for aneurysmal subarachnoid hemorrhage in 2017. This study was conducted to determine whether the SAFARI score derived from the afore-mentioned study could be applied to patients with aneurysmal subarachnoid hemorrhage in Korea. Methods: We conducted a retrospective study of patients who were diagnosed with aneurysmal subarachnoid hemorrhage from March 2013 to October 2017. Patients' age, sex, blood pressure, pulse rate, body temperature, Glasgow-Coma Scale, Hunt-Hess scale, modified Fisher grade, size of ruptured aneurysm, surgery type, transfusion, and SAFARI score were compared between the seizure and non-seizure groups. The area under the receiver operator characteristic curves was calculated to evaluate the predictive ability for seizure during admission. Logistic regression analysis was used to analyze predictive factors for seizure during admission. Results: A total of 220 patients were included. Ninety-seven (44.1%) were male and 123 (55.9%) were female. The mean age of the patients was 65.8 years old (range, 56-75). The area under the curve of the SAFARI score for predicting seizure was 0.813. The SAFARI score was the only significant predictor of seizure during admission, while other factors were not statistically significant upon logistic regression analysis. Conclusion: The SAFARI score could be used for predicting seizure during admission in patients with aneurysmal subarachnoid hemorrhage.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1281-1289
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• 2022

Objective: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. Materials and Methods: A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. Results: The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. Conclusion: Radiomic models using MRI were able to differentiate JME from HCs.

• Journal of Environmental Impact Assessment
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• v.22 no.3
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• pp.219-230
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• 2013

Species distribution modeling is one of the most effective habitat analysis methods for wildlife conservation. This study was for evaluating the suitability of species distribution to distance between forest patches in Seoul city using tits. We analyzed the distribution of the four species of tits: varied tit (Parus varius), marsh tit (P. palustris), great tit (P. major) and coal tit (P. ater), using the landscape indexes and connectivity indexes, and compared the resulting suitability indexes from 100m to 1,000m. As factors affecting to the distribution of tits, we calculated landscape indices by separating them into intra-patch indices (i.e. logged patch area (PA), area-weighted mean patch shape index (PSI), tree rate (TR)) and inter-patch indices (i.e. patch degree (PD), patch betweenness (PB), difference probability of connectivity (DPC)), to analyze the internal properties of the patches and their connectivity by tits occurrence data using logistic regression modeling. The models were evaluated by AICc (Akaike Information Criteria with a correction for finite sample sizes) and AUC (Area Under Curve of ROC). The results of AICc and AUC showed DPC, PA, PSI, and TR were important factors of the habitat models for great tit and marsh tit at the level of distance 500~800m. In contrast, habitat models for coal tit and varied tit, which are known as forest interior species, reflected PA, PSI, and TR as intra-patch indices rather than connectivity. These mean that coal tit and varied tit are more likely to find a large circular forest patch than a small and long-shaped forest patch, which are higher rate of forest. Therefore, different strategies are required in order to enhance the habitats of the forest birds, tits, in a region that has fragmented forest patches such as Seoul city. It is important to manage forest interior areas for coal tit and varied tit, which are known as forest interior species and to manage not only forest interior areas but also connectivity of the forest patches in the threshold distance for great tit and marsh tit as adapted species to the urban ecosystem for sustainable ecosystem management.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Korean Journal of Radiology
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• v.24 no.5
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• pp.395-405
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• 2023

Objective: This study aimed to develop and validate models using radiomics features on a native T1 map from cardiac magnetic resonance (CMR) to predict left ventricular reverse remodeling (LVRR) in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods: Data from 274 patients with NIDCM who underwent CMR imaging with T1 mapping at Severance Hospital between April 2012 and December 2018 were retrospectively reviewed. Radiomic features were extracted from the native T1 maps. LVRR was determined using echocardiography performed ≥ 180 days after the CMR. The radiomics score was generated using the least absolute shrinkage and selection operator logistic regression models. Clinical, clinical + late gadolinium enhancement (LGE), clinical + radiomics, and clinical + LGE + radiomics models were built using a logistic regression method to predict LVRR. For internal validation of the result, bootstrap validation with 1000 resampling iterations was performed, and the optimism-corrected area under the receiver operating characteristic curve (AUC) with 95% confidence interval (CI) was computed. Model performance was compared using AUC with the DeLong test and bootstrap. Results: Among 274 patients, 123 (44.9%) were classified as LVRR-positive and 151 (55.1%) as LVRR-negative. The optimism-corrected AUC of the radiomics model in internal validation with bootstrapping was 0.753 (95% CI, 0.698-0.813). The clinical + radiomics model revealed a higher optimism-corrected AUC than that of the clinical + LGE model (0.794 vs. 0.716; difference, 0.078 [99% CI, 0.003-0.151]). The clinical + LGE + radiomics model significantly improved the prediction of LVRR compared with the clinical + LGE model (optimism-corrected AUC of 0.811 vs. 0.716; difference, 0.095 [99% CI, 0.022-0.139]). Conclusion: The radiomic characteristics extracted from a non-enhanced T1 map may improve the prediction of LVRR and offer added value over traditional LGE in patients with NIDCM. Additional external validation research is required.