• Journal of Gastric Cancer
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• v.21 no.4
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• pp.368-378
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• 2021

Purpose: When patients with early gastric cancer (EGC) undergo non-curative endoscopic submucosal dissection requiring gastrectomy (NC-ESD-RG), additional medical resources and expenses are required for surgery. To reduce this burden, predictive model for NC-ESD-RG is required. Materials and Methods: Data from 2,997 patients undergoing ESD for 3,127 forceps biopsy-proven differentiated-type EGCs (2,345 and 782 in training and validation sets, respectively) were reviewed. Using the training set, the logistic stepwise regression analysis determined the independent predictors of NC-ESD-RG (NC-ESD other than cases with lateral resection margin involvement or piecemeal resection as the only non-curative factor). Using these predictors, a risk-scoring system for predicting NC-ESD-RG was developed. Performance of the predictive model was examined internally with the validation set. Results: Rate of NC-ESD-RG was 17.3%. Independent pre-ESD predictors for NC-ESD-RG included moderately differentiated or papillary EGC, large tumor size, proximal tumor location, lesion at greater curvature, elevated or depressed morphology, and presence of ulcers. A risk-score was assigned to each predictor of NC-ESD-RG. The area under the receiver operating characteristic curve for predicting NC-ESD-RG was 0.672 in both training and validation sets. A risk-score of 5 points was the optimal cut-off value for predicting NC-ESD-RG, and the overall accuracy was 72.7%. As the total risk score increased, the predicted risk for NC-ESD-RG increased from 3.8% to 72.6%. Conclusions: We developed and validated a risk-scoring system for predicting NC-ESD-RG based on pre-ESD variables. Our risk-scoring system can facilitate informed consent and decision-making for preoperative treatment selection between ESD and surgery in patients with EGC.

• Journal of Korean Society of Forest Science
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• v.86 no.2
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• pp.135-145
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• 1997

This study aimed at evaluating one curvilinear equation and nine non-linear equations for estimating stand growth characteristics(mean dbh, mean height and volume per ha) for the plantations of Pinus koraiensis and the natural stands of Quercus mongolica. The data were collected from 92 plots in Pines koraiensis stands and 83 plots in Quercus mongolica stands, and the site index of all the stands is 14. The curvilinear equation, $Y=at^be^{-c/t}$, used in preparing the yield tables was well fitted within the range of data, but was likely to give overestimates when extrapolating in old stage due to the tendency of linear increase. Among the non-linear equations, logistic equation and Sloboda equation gave overestimates in young stands and reached the asymptotic status early which means underestimates in old stage. Extrapolating in old stage, Hossfeld equation generally gave larger values than others due to its large estimates of parameter a, the maximum value. On the other hand, Bertalanffy equation gave underestimates in young and old stands and overestimates in middle-aged stands. The estimates with Korf equation was relatively low for Pinus koraiensis stands, and this tendency was more obvious in dbh growth of Quercus mongolica stands. Ueno-Ohzaki equation was liable to give over or underestimates depending on the value of parameter b when extrapolating in old stands. Considering the accuracy of estimates and the biological base of the growth equations, Gompertz equation, Chapman-Richards equation and Weibull equation were generally applicable for estimating the stand growth characteristics of both species in the whole range of stand ages including extrapolated range. To get more accurate and precise parameter estimates, more data, especially in old stands, should be required in further study.

• Investigative Magnetic Resonance Imaging
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• v.18 no.2
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• pp.120-132
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• 2014

Purpose : To compare dynamic susceptibility contrast imaging, diffusion-weighted imaging, and susceptibility-weighted imaging (SWI) for the differentiation of tumor recurrence and delayed radiation therapy (RT)-related changes in patients treated with RT for primary brain tumors. Materials and Methods: We enrolled 24 patients treated with RT for various primary brain tumors, who showed newly appearing enhancing lesions more than one year after completion of RT on follow-up MRI. The enhancing-lesions were confirmed as recurrences (n=14) or RT-changes (n=10). We calculated the mean values of normalized cerebral blood volume (nCBV), apparent diffusion coefficient (ADC), and proportion of dark signal intensity on SWI (proSWI) for the enhancing-lesions. All the values between the two groups were compared using t-test. A multivariable logistic regression model was used to determine the best predictor of differential diagnosis. The cutoff value of the best predictor obtained from receiver-operating characteristic curve analysis was applied to calculate the sensitivity, specificity, and accuracy for the diagnosis. Results: The mean nCBV value was significantly higher in the recurrence group than in the RT-change group (P=.004), and the mean proSWI was significantly lower in the recurrence group (P<.001). However, no significant difference was observed in the mean ADC values between the two groups. A multivariable logistic regression analysis showed that proSWI was the only independent variable for the differentiation; the sensitivity, specificity, and accuracy were 78.6% (11 of 14), 100% (10 of 10), and 87.5% (21 of 24), respectively. Conclusion: The proSWI was the most promising parameter for the differentiation of newly developed enhancing-lesions more than one year after RT completion in brain tumor patients.

• Journal of Korean Society of Forest Science
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• v.34 no.1
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• pp.21-30
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• 1977

Japanese larch (Larix leptolepis) is one of main timber species in Korea that could find much plantation and growing stands on all over the country. It is thought to be in meaningful that a guiding diagram for density control of Japanese larch stands is made to estimate easily the density conditions in the quantitaive, ecological and economic viewpoint. Sample plots for this study are selected from the stands that have not been thinned in recent years, and mean height, mean diameter, dominant height, tree numbers per hectare and stem volume of mean tree are calculated from the each sample plots among total 165 plots In this study, especially, the theory of slenderness of mean tree are applied, that have been identified through the results of the spacing trial. Relative growth characteristics of this species are calculated from the general logistic curve and its formula is $Y=ax^b$. Relatwion between the measured items are found out as follows: 1. Relation between the mean height and tree numbers per hectare by slender class is showing the high correlation as table 1 and fig. 2, and between mean diameter and tree numbers per hectare is also high correlation as table 1 and fig 3. 2. The stem volume can be correctly estimated from height in case that slender class may be known, as showing in table 3 and fig. 4. 3. The stem volume can be more correctly estimated from the relation with $D^2H$ as formula, $Log_e\;V=0.9569\;Log_eD^2H-9.8431$, and relation between stem volume of single tree or volume per hectare and tree numbers per hectare are as following formulas: $Log_e$ stem volume=9.5026-1.6800 $Log_e$ tree numbers per hectare $Log_e$ stem volume per hectare=9.4911-0.6784 $Log_e$ tree numbers per hectare. Stem volume of mean tree, tree numbers per hectare and stem volume per hectare correspond to the mean tree height are calculated to slender class as table 5, 6, 7. Through the above steps, the diagram for density control of Japanese larch are produced as fig. 9. It is thought that this diagram could be applied to control the density of Japanese larch stands.

• Tuberculosis and Respiratory Diseases
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• v.56 no.6
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• pp.600-610
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• 2004

Background : The plasma B-type natriuretic peptide(BNP) concentration increases with the degree of pulmonary hypertension in patients with chronic respiratory disease. The aim of this study was to examine the prognostic role of BNP in the acute exacerbation of chronic obstructive lung disease (COPD). Method : We selected 67 patients who were admitted our hospital because of an acute exacerbation of COPD. Their BNP levels were checked on admission at the Emergency Department. Their medical records were analyzed retrospectively. The patients were divided into two groups according to their in-hospital mortality. The patients' medical history, comobidity, exacerbation type, blood gas analysis, pulmonary function, APACHE II severity score and plasma BNP level were compared. Results : Multiple logistic regression analysis identified three independent predictors of mortality: $FEV_1$, APACHE II score and plasma BNP level. The decedents group showed a lower $FEV_1$($28{\pm}7$ vs. $37{\pm}15%$, p=0.005), a higher APACHE II score($22.4{\pm}6.1$ vs. $15.8{\pm}4.7$, p=0.000) and a higher BNP level ($201{\pm}116$ vs. $77{\pm}80pg/mL$, p=0.000) than the sSurvivors group. When the BNP cut-off level was set to 88pg/mL using the receiver operating characteristic curve, the sensitivity was 90% and the specificity was 75% in differentiating between the survivors and decedents. On Fisher's exact test, the odds ratio for mortality was 21.2 (95% CI 2.49 to 180.4) in the patients with a BNP level > 88pg/mL. Conclusion : The plasma BNP level might be a predictor of mortality in an acute exacerbation of COPD as well as the $FEV_1$ and APACHE II score.

• Journal of dental hygiene science
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• v.17 no.1
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• pp.38-45
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• 2017

We evaluated the association between sleep duration, dental caries, and periodontitis by using representative nationwide data. We examined 8,356 subjects aged ${\geq}19$ years who participated in the sixth Korea National Health and Nutrition Examination Survey (2013~2014). Sleep duration were grouped into ${\leq}5$, 6, 7, 8, and ${\geq}9$ hours. Presence of dental caries was defined as caries in ${\geq}1$ permanent tooth on dental examination. Periodontal status was assessed by using the community periodontal index (CPI), and a CPI code of ${\geq}3$ was defined as periodontitis. A chi-square test and multiple logistic regression analysis were used to determine statistical significance. Model 1 was adjusted for age and sex, model 2 for household income, educational level, and marital status plus model 1, and model 3 for smoking status, alcohol consumption, blood pressure level, fasting blood glucose level, total cholesterol level, and body mass index plus model 2. The prevalence of dental caries according to sleep duration showed a U-shaped curve of 33.4%, 29.4%, 28.4%, 29.4%, and 31.8% with ${\leq}5$, 6, 7, 8, and ${\geq}9$ hours of sleep, respectively. In the fully adjusted model 3, the risk of developing dental caries was significantly higher with ${\leq}5$ than with 7 hours of sleep (odds ratio, 1.23; 95% confidence interval, 1.06~1.43). The prevalence of periodontitis according to sleep duration showed a U-shaped curve of 34.4%, 28.6%, 28.1%, 31.3%, and 32.5%, respectively. The risk of periodontitis was significantly higher with ${\geq}9$ than with 7 hours of sleep in models 1 and 2, whereas the significant association disappeared in model 3. In a nationally representative sample, sleep duration was significantly associated with dental caries formation and weakly associated with periodontitis. Adequate sleep is required to prevent oral diseases such as dental caries and periodontitis.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.25 no.1
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• pp.77-86
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• 1980

Asking to change the cropping patterns to save the labor and capitals in paddy rice cultivation, the study was intended to know the weed problems under the various possible cultural systems; namely, direct seeding (in broadcast and row), machine transplanting and hand transplanting. Under the conditions as weedy check plots, paddy yields were significantly variated among cropping systems, and the functions of panicle No. and spikelet No. to the yield were neglected, among others. However, the yield and yield components were narrowed among cropping systems, and the function of spikelets number per area was comparatively improved to the others.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Pediatric Infection and Vaccine
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• v.16 no.2
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• pp.142-149
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• 2009

Purpose : The aim of this study was to determine the diagnostic value of serum procalcitonin (PCT) compared with that of C-reactive protein (CRP) and the total white blood cell count (WBC) in predicting bacterial infections in febrile infants<6 months of age. Methods : A prospective study was performed with infants <6 months of age who were admitted to the Department of Pediatrics with a fever of uncertain source between July and September 2008. Spinal taps were performed according to clinical symptoms and physical examination. Serum PCT levels were measured using an enzyme-linked fluorescent assay. Results : Seventy-one infants (mean age, 2.62 months) were studied. Twenty-six infants (36.6%) had urinary tract infections (UTIs), and 22 infants (31.0%) had viral meningitis. The remaining infants had acute pharyngitis (n=1), herpangina (n=1), upper respiratory tract infections (n=7), acute bronchiolitis (n=8), acute gastroenteritis (n=4), and bacteremia (n=2). The median WBC and CRP levels were significantly higher in infants with UTIs than in infants with viral meningitis. However, there were no differences in the median PCT levels between the groups (0.14 ng/mL vs. 0.11 ng/mL, P=0.419). The area under the receiver operating characteristic curve was 0.792 (95% CI, 0.65-0.896) for WBC, 0.77 (95% CI, 0.626-0.879) for CRP, and 0.568 (95% CI, 0.417-0.710) for PCT. An elevated WBC count (>11,920/${\mu}L$) and an increased CRP level (>1.06mg/dL) were significant predictors of UTIs based on multiple logistic regression analysis. Conclusion : Serum PCT concentrations should be interpreted with caution in infants <6 months of age with a fever of uncertain source.

• Tuberculosis and Respiratory Diseases
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• v.45 no.4
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• pp.746-753
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• 1998

Background : Cigarette smoking is closely related to both lung cancer and chronic obstructive pulmonary disease. The incidence of lung cancer is higher in patients with obstructive ventilatory impairment than in patients without obstructive ventilatory impairment regardless of smoking. So, obstructive ventilatory impairment is suspected as an independent risk factor of lung cancer. Methods: For the evaluation of the role of obstructive ventilatory impairment as a risk factor of lung cancer, a total of 73 cases comprising 47 cases of malignant and 26 benign solitary pulmonary nodule were analyzed retrospectively. A comparative study of analysis of forced expiratory volume curves and frequencies of obstructive ventilatory impairment were made between cases with malignant and benign nodules. Results: In comparison of vital capacity and parameters derived from forced expiratory volume curve between two groups. VC, FVC and $FEV_1$ were not significantly different. whereas $FEV_1/FVC%$ and FEF 25-75% showed a significant decrease in the cases with malignant nodule. The frequency of obstructive ventilatory impairment determined by pulmonary function test was significantly higher in the cases with malignant nodule(23.4%) than in benign nodule(3.8%). When the risk for lung cancer was examined by the presence or absence of obstructive ventilatory impairment using the logistic regression analysis, the unadjusted relative risk for the lung cancer of obstructive ventilatory impairment was 17.17. When the effect of smoking and age were considered, the relative risk was to 8.13. Conclusion: These findings suggest that an obstructive ventilatory impairment is a risk factor of lung cancer.