• Nutrition Research and Practice
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• v.11 no.4
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• pp.300-306
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• 2017

BACKGROUND/OBJECTIVES: The doubly labeled water (DLW) method is considered the gold standard for the measurement of total energy expenditure (TEE), which serves to estimate energy requirements. This study evaluated the accuracy of predictive dietary reference intake (DRI) equations for determining the estimated energy requirements (EER) of Korean adults by using the DLW as a reference method. SUBJECTS/METHODS: Seventy-one participants (35 men and 36 women) aged between 20 and 49 years were included in the study. The subjects' EER, calculated by using the DRI equation ($EER_{DRI}$), was compared with their TEE measured by the DLW method ($TEE_{DLW}$). RESULTS: The DRI equations for EER underestimated TEE by -36.3 kcal/day (-1.3%) in men and -104.5 kcal/day (-4.9%) in women. The percentages of accurate predictions among subjects were 77.1% in men and 62.9% in women. There was a strong linear correlation between $EER_{DRI}$ and $TEE_{DLW}$ (r = 0.783, P < 0.001 in men and r = 0.810, P < 0.001 in women). CONCLUSIONS: The present study supports the use of DRI prediction equations to determine EER in Korean adults. More studies are needed to confirm our results and to assess the validity of these equations in other population groups, including children, adolescents, and older adults.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.332-337
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• 2006

It has been suggested that the endoscopic color of intramucosal gastric carcinoma is correlated with mucosal vascularity within the carcinomatous tissue. The development of electronic endoscopy has made it possible to quantitatively measure the mucosal hemoglobin volume, using a hemoglobin index. The aim of this study was to make a software program to calculate the hemoglobin index (IHb) and then investigate whether the mucosal IHb determined from the electronic endoscopic data is a useful marker for evaluating the color of intramucosal gastric carcinoma, in particular with regard to its value for discriminating between the histologic types. The mean values of IHb for the carcinoma (IHb-C) and the mean values of IHb for the surrounding non-cancerous mucosa (IHb-N) were calculated in 75 intestinal-type and 34 diffuse-type gastric carcinomas. Then, we analyzed the ratio of the IHb-C to IHb-N. The mean IHb-C/IHb-N ratio in the intestinal-type carcinoma group was higher than that in the diffuse-type carcinoma group (1.28$\pm$0.19 vs. 0.81$\pm$0.18, respectively, p<0.001). When the cut-off point of the C/N ratio was set at 1.00, the accuracy rate, the sensitivity, the specificity, and the positive and negative predictive values of a C/R ratio below 1.00 for the differential diagnosis of diffuse-type carcinoma from intestinal-type carcinoma were 94.5%, 94.1%, 94.7%, 88.9% and 97.3%, respectively. IHb is useful for quantitative measurement of the endoscopic color in intramucosal gastric carcinoma and the IHb-C/IHb-N ratio would be helpful in distinguishing diffuse-type carcinoma from intestinal-type carcinoma.

• Korea Real Estate Review
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• v.27 no.3
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.497-508
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• 2019

Purpose: The purpose of this study is to overcome limitations of conventional studies that to predict Baltic Dry Index (BDI). The study proposed applications of Artificial Neural Network (ANN) named Long Short-Term Memory (LSTM) to predict BDI. Methods: The BDI time-series prediction was carried out through eight variables related to the dry bulk market. The prediction was conducted in two steps. First, identifying the goodness of fitness for the BDI time-series of specific ANN models and determining the network structures to be used in the next step. While using ANN's generalization capability, the structures determined in the previous steps were used in the empirical prediction step, and the sliding-window method was applied to make a daily (one-day ahead) prediction. Results: At the empirical prediction step, it was possible to predict variable y(BDI time series) at point of time t by 8 variables (related to the dry bulk market) of x at point of time (t-1). LSTM, known to be good at learning over a long period of time, showed the best performance with higher predictive accuracy compared to Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN). Conclusion: Applying this study to real business would require long-term predictions by applying more detailed forecasting techniques. I hope that the research can provide a point of reference in the dry bulk market, and furthermore in the decision-making and investment in the future of the shipping business as a whole.

• Journal of Environmental Health Sciences
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• v.45 no.5
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• pp.457-464
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• 2019

Objectives: Quantitative structure-activity relationship (QSAR) is one of the effective alternatives to animal testing, but its credibility in terms of toxicity prediction has been questionable. Thus, this work aims to evaluate its predictive capacity and find ways of improving its credibility. Methods: Using $TOPKAT^{(R)}$, OECD toolbox, and $Derek^{(R)}$, all of which have been applied world-wide in the research, industrial, and regulatory fields, an analysis of prediction credibility markers including accuracy (A), sensitivity (S), specificity (SP), false negative (FN), and false positive (FP) was conducted. Results: The multi-application of QSARs elevated the precision credibility relative to individual applications of QSARs. Moreover, we found that the type of chemical structure affects the credibility of markers significantly. Conclusions: The credibility of individual QSAR is insufficient for both the prediction of chemical toxicity and regulation of hazardous chemicals. Thus, to increase the credibility, multi-QSAR application, and compensation of the prediction deviation by chemical structure are required.

• Journal of Environmental Health Sciences
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• v.45 no.5
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• pp.511-519
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• 2019

Objectives: The standard method for the enumeration of environmental Legionella is culturing, which has several disadvantages, including long incubation and poor sensitivity. The purpose of this study is to demonstrate the usefulness of real-time PCR and to improve the standard method. Methods: In 200 environmental water samples, a real-time PCR and culture were conducted to detect and quantify Legionella. Using with the results of the survey, we compared the real-time PCR with the culture. Results: Each real-time PCR assay had 100% specificity and excellent sensitivity (5 GU/reaction). In the culture, 36 samples were positive and 164 samples were negative. Based on the results of the culture, real-time PCR showed a high negative predictive value of 99%, 35 samples were true positive, 105 samples were true negative, 59 samples were false positive and one sample was a false negative. Quantitative analysis of the two methods indicated a weak linear correlation ($r^2=0.29$, $r^2=0.61$, respectively). Conclusions: Although it is difficult to directly apply quantitative analysis results of real-time PCR in the enumeration of environmental Legionella, it can be used as a complementary means of culturing to rapidly screen negative samples and to improve the accuracy of diagnosis.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.83-91
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• 2021

For agricultural products, supply is irregular due to changes in meteorological conditions, and it has high price elasticity. For example, if the supply decreases by 10%, the price increases by 50%. Due to these fluctuations in the prices of agricultural products, the Korean government guarantees the safety of prices to producers through small merchants' auctions. However, when prices plummet due to overproduction, protection measures for producers are insufficient. Therefore, in this paper, we designed a business model that can be used in the electronic transaction system by predicting the price of agricultural products with an artificial intelligence algorithm. To this end, the trained model with the training pattern pairs and a predictive model was designed by applying ARIMA, SARIMA, RNN, and CNN. Finally, the agricultural product forecast price data was classified into short-term forecast and medium-term forecast and verified. As a result of verification, based on 2018 data, the actual price and predicted price showed an accuracy of 91.08%.

• Clinical and Experimental Pediatrics
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• v.64 no.7
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• pp.347-354
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• 2021

Background: Neutrophil gelatinase-associated lipocalin (NGAL) has emerged as a valuable biomarker of urinary tract infection (UTI) in children. Purpose: This study aimed to compare the diagnostic accuracy of urinary NGAL (uNGAL) with those of serum C-reactive protein (CRP) and white blood cell (WBC) count for predicting UTI and acute pyelonephritis (APN) in febrile children. Methods: The medical charts of children undergoing uNGAL measurements between November 2017 and August 2019 were retrospectively reviewed. Patients with a suspected or diagnosed UTIs were included. The diagnostic accuracies of uNGAL, serum CRP, and WBC count for detecting UTI and APN were investigated. Independent predictors of UTI and APN were investigated using multivariable logistic regression analyses. Results: A total of 321 children were enrolled in this study. The uNGAL levels were higher in the UTI group (n=157) than in the non-UTI group (n=164) (P<0.05). Among children with a UTI, uNGAL levels were higher in the APN group (n=70) than, the non-APN group (n=87) (P<0.05). In the multivariate analysis, uNGAL was independently associated with UTI and APN (both P<0.05). Serum CRP and WBC count were not correlated with the presence of UTI and APN. Receiver operating curve analyses showed that the uNGAL level had the highest area under the curve (AUC) for predicting UTI and APN, respectively (AUC, uNGAL vs. CRP vs. WBC count, 0.860 vs. 0.608 vs. 0.669 for UTI; 0.780 vs. 0.680 vs. 0.639 for APN, all P<0.05, respectively). The predictive values and likelihood ratios of uNGAL were superior to those of serum CRP and WBC count for detecting UTI and APN at each cutoff level. Conclusion: UNGAL may be more useful than serum CRP and WBC count for identifying and assessing UTI in febrile children.

• Korean Journal of Clinical Oncology
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• v.14 no.2
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• pp.135-141
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• 2018

Purpose: Axillary lymph node dissection (ALND) and sentinel lymph node biopsy (SLNB) are important for staging of patients with node-positive breast cancer. However, these can be avoided in select micrometastatic diseases, preventing postoperative complications. The present study evaluated the ability of axillary lymph node maximum standardized uptake value (SUVmax) on positron emission tomography-computed tomography (PET-CT) to predict axillary metastasis of breast cancer. Methods: The records of invasive breast cancer patients who underwent pretreatment (surgery and/or chemotherapy) PET-CT between January 2006 and December 2014 were reviewed. ALNs were preoperatively evaluated by PET-CT. Lymph nodes were dissected by SLNB or ALND. SUVmax was measured in both the axillary lymph node and primary tumor. Student t-test and chi-square test were used to analyze sensitivity and specificity. Receiver operating characteristic (ROC) and area under the ROC curve (AUC) analyses were performed. Results: SUV-tumor (SUV-T) and SUV-lymph node (SUV-LN) were significantly higher in the triple-negative breast cancer (TNBC) group than in other groups (SUV-T: 5.99, P<0.01; SUV-LN: 1.29, P=0.014). The sensitivity (0.881) and accuracy (0.804) for initial ALN staging were higher in fine needle aspiration+PET-CT than in other methods. For PET-CT alone, the subtype with the highest sensitivity (0.870) and negative predictive value (0.917) was TNBC. The AUC for SUV-LN was greatest in TNBC (0.797). Conclusion: The characteristics of SUV-T and SUV-LN differed according to immunohistochemistry subtype. Compared to other subtypes, the true positivity of axillary metastasis on PET-CT was highest in TNBC. These findings could help tailor management for therapeutic and diagnostic purposes.

• Asian Spine Journal
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• v.12 no.6
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• pp.1069-1077
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• 2018

Study Design: A case study. Purpose: To assess the chronological changes of the disease-related kyphosis after chemotherapy alone, secondly to clarify the role of growth cartilage in the healed lesion on kyphosis change, and to define the accurate prediction time in assessing residual kyphosis. Overview of Literature: None of the previous papers up to now dealt with the residual kyphosis, stability and remodeling processes of the affected segments. Methods: One hundred and one spinal tuberculosis children with various stages of disease processes, age 2 to 15 years, were the subject materials, between 1971 to 2010. They were treated with two different chemotherapy formula: before 1975, 18 months of triple chemotherapy (isoniazid [INH], para-aminosalicylic acid, streptomycin); and since 1976, 12 months triple chemotherapy (INH, rifampicin, ethambutol, or pyrazinamide). The first assessment at post-chemotherapy one year and at the final discharge time from the follow-up (36 months at minimum and 20 years at maximum) were analyzed by utilizing the images effect of the remaining growth plate cartilage on chronological changes of kyphosis after initiation of chemotherapy. Results: Complete disc destruction at the initial examination were observed in two (5.0%) out of 40 cervical spine, eight (26.7%) out of 30 dorsal spine, and six (19.4%) out of 31 lumbosacral spine. In all those cases residual kyphosis developed inevitably. In the remainders the discs were partially preserved or remained intact. Among 101 children kyphosis was maintained without change in 20 (19.8%), while kyphosis decreased in 14 children (13.7%), and increased in 67 children (66.3%) with non-recoverably damaged growth plate, respectively. Conclusions: It could tentatively be possible to predict the deformity progress or non-progress and spontaneous correction at the time of initial treatment, but it predictive accuracy was low. Therefore, assessment of the trend of kyphotic change is recommended at the end of chemotherapy. In children with progressive curve change, the deformity assessment should be continued till the maturity.