• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.28 no.4
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• pp.371-379
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• 1992

In order to analyse the mesh selectivity for the trawl net, the fishing experiment was carried out by the training ship Saebada in the southern Korea Sea and the East China Sea from June 1991 to August 1992. The trawl net used in experiment has the trouser type of cod-end with cover net, and the mesh selectivity was examined for the five kinds of the opening mesh size in its cod-end part. The selection curves and the selection parameters were calculated by using a logistic function, S=1/(1+exp super(-(aL+b))), and in this case, a and b are the selection parameters and L is the body length of the target species of fishes. In this report, the four species of aquatic animals were analysed because the catch data were enough to calculate normally the selection curves and the selection parameters, and the results obtained are summarized as follows: 1. Trachurus japonicus; Selection parameters a and b in each cases of the opening mesh size of 51.2mm, 70.2mm, 77.6mm, 88.0mm and 111.3mm were respectively 0.5050 and -5.4283, 0.3018 and -4.9590, 0.3816 and -7.3659, 0.2695 and -5.7958, 0.2170 and -5.1226. 2. Photololigo edulis ; Selection Parameters a and b in each cases of the former mesh sizes were respectively 0.7394 and -6.1433, 0.3389 and -4.2366, 0.3286 and -5.1002, 0.2543 and -5.0049, 0.1795 and -4.8040. 3. Trichirus lepturus; Selection curves in the opening mesh size of 111.3mm was calculated unnormally. The selection parameters in the other opening mesh sizes were respectively 0.3790 and -5.2891, 0.2071 and -4.9164, 0.1292 and -3.1733, 0.1153 and -3.8497 in the order of former mesh sizes except 111.3mm. 4. Todarodes pacificus ; Selection curve in case of the opening mesh sizes, 70.2mm and 111.3mm were calculated unnormally. In the order cases of the opening mesh sizes, the selection parameters were respectively were 0.5766 and -6.0169, 0.3735 and -5.4633, 0.2771 and -5.7718 in the order of former mesh sizes except 70.2mm and 111.3mm.

• Tuberculosis and Respiratory Diseases
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• v.81 no.3
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• pp.247-255
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• 2018

Background: Patients with acute respiratory failure secondary to tuberculous destroyed lung (TDL) have a poor prognosis. The aim of the present retrospective study was to develop a mortality prediction model for TDL patients who require mechanical ventilation. Methods: Data from consecutive TDL patients who had received mechanical ventilation at a single university-affiliated tertiary care hospital in Korea were reviewed. Binary logistic regression was used to identify factors predicting intensive care unit (ICU) mortality. A TDL on mechanical Ventilation (TDL-Vent) score was calculated by assigning points to variables according to ${\beta}$ coefficient values. Results: Data from 125 patients were reviewed. A total of 36 patients (29%) died during ICU admission. On the basis of multivariate analysis, the following factors were included in the TDL-Vent score: age ${\geq}65$ years, vasopressor use, and arterial partial pressure of oxygen/fraction of inspired oxygen ratio <180. In a second regression model, a modified score was then calculated by adding brain natriuretic peptide. For TDL-Vent scores 0 to 3, the 60-day mortality rates were 11%, 27%, 30%, and 77%, respectively (p<0.001). For modified TDL-Vent scores 0 to ${\geq}3$, the 60-day mortality rates were 0%, 21%, 33%, and 57%, respectively (p=0.001). For both the TDL-Vent score and the modified TDL-Vent score, the areas under the receiver operating characteristic curve were larger than that of other illness severity scores. Conclusion: The TDL-Vent model identifies TDL patients on mechanical ventilation with a high risk of mortality. Prospective validation studies in larger cohorts are now warranted.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.5095-5099
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• 2015

Background: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. Materials and Methods: A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. Results: The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05%(200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (${\geq}65$ years), use of antibiotics, low serum albumin concentrations (${\leq}37.18g/L$), radiotherapy, surgery, low hemoglobin hyperlipidemia (${\leq}93.67g/L$), long time of hospitalization (${\geq}14$days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model($0.829{\pm}0.019$)was higher than that of LR model ($0.756{\pm}0.021$). Conclusions: The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.

• Child Health Nursing Research
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• v.19 no.1
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• pp.12-20
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• 2013

Purpose: The purpose of this study was to investigate factors associated with suspicious developmental delay in infants and early childhood. Methods: Participants were 133 infants, aged from birth to 6 years old and their mothers, who were being seen at 16 Public health centers in B city. Korean Denver II was used to test infant development. ${\chi}^2$-test, Fisher's exact test and multiple logistic regression were used with SPSS 19.0 to analyze data. Results: Of participant infants, 7.5% were below the 3rd percentile for the weight percentile, 8.4% is a weight curve that crosses more than 2 percentile lines on the growth charts after previous achievement, and 9.8% had suspicious developmental delay according to Korean Denver II. Further the predictive factors related to suspicious development delay in the children were decrease of weight percentile (Odds Ratio [OR]=6.69, Confidence Interval [CI])=1.22-36.45), low economic state (OR=6.26, CI=1.50-26.00), and development delay perceived by their mothers (OR=4.99, CI=1.24-20.06). Conclusion: It is necessary to build a government level system to follow management of development of infants and children from the time of birth. Especially, it is necessary to develop a program for children in low income families.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.43-52
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• 2012

A lane departure warning system (LDWS) is an effective technology-based countermeasure for preventing traffic crashes as it provides warning information to drivers. Understanding the characteristics of perception and satisfaction levels on LDWS is fundamental for deriving better performance and functionality enhancements of the system. The purpose of this study is to evaluate the user satisfaction of LDWS. A survey to collect user perception and user preference data was conducted. Both cross-tabulation analysis and binary logistic regression technique were adopted to identify the factors affecting user satisfaction for LDWS. The results revealed that the accuracy and timeliness of warning information was significant for evaluating the effectiveness of LDWS. In particular, the warning accuracy at a curve segment on the road was the most dominant factor affecting user satisfaction. The outcome of this study would be valuable in evaluating and designing LDWS functionalities.

• Journal of the Korean Society of Radiology
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• v.10 no.3
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• pp.187-193
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• 2016

In this study, we performed the carotid artery ultrasound targeting 140 subjects who have conducted to evaluate the changes in intima-media thickness(IMT) and plaque correlated with the presence or absence of a hematological test of the carotid artery. Considering that the IMT thickness more than 1mm is abnormal based on the carotid artery ultrasound to assess the presence or absence of plaque, and examined the correlation by classifying the blood lipid value and the fasting blood glucose level through the serum test. Consequently, the fasting blood glucose level is being analyzed as independent predictors of causing dental plaque(p=0.033), cut off value was determined as 126 mg/dL(sensitivity 56.25%, specificity 68.38%) in ROC curve analysis. Furthermore, the odds ratio appeared 1.01 times the value in the Logistic regression. Therefore, it seemed that the necessity to prospective studies in a number of subjects are considered, and also taking into account a number of blood test values along with the sonography of the carotid artery as a valuable part for effective primary prevention and follow-up observation of the cardiac and brain vascular disease is highly recommended.

• Korean Journal of Psychosomatic Medicine
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• v.23 no.2
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• pp.114-120
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• 2015

Objectives : This study aimed to investigate the risk factors of depression for patients with tuberculosis(TB). Methods : A total of 57 patients with TB were recruited. All participants completed the Becks Depression Inventory-II for evaluating depressive symptoms. The risk factor for depression was analyzed by binary logistic regression analysis. Nomogram was performed for probability of depression. Results : Low body mass index(BMI, OR 0.801, 95% CI 0.65, 0.98), interruption of treatment for TB(OR 5.908, 95% CI 1.19, 29.41), past history of depression(OR 24.653, 95% CI 1.99, 308.44) were associated with increased risk for depression. The calibration curve for predicting probability of survival showed a good agreement between the nomogram and actual observation(Original C-index=0.789, bias corrected C-index=0.754). Conclusions : The result of the present study indicate that low BMI, interruption of treatment for TB, and past history of depression were risk factors for depression in patients with TB. The psychiatric intervention may be needed to prevent depression if the patients with TB have risk factor during treatment for TB.

• Journal of Breast Disease
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• v.6 no.2
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• pp.52-59
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• 2018

Purpose: This study aimed to determine whether clinicopathological factors are potentially associated with successful breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NAC) and develop a nomogram for predicting successful BCS candidates, focusing on those who are diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative tumors during the pre-NAC period. Methods: The training cohort included 239 patients with an HR-positive, HER2-negative tumor (${\geq}3cm$), and all of these patients had received NAC. Patients were excluded if they met any of the following criteria: diffuse, suspicious, malignant microcalcification (extent >4 cm); multicentric or multifocal breast cancer; inflammatory breast cancer; distant metastases at the time of diagnosis; excisional biopsy prior to NAC; and bilateral breast cancer. Multivariate logistic regression analysis was conducted to evaluate the possible predictors of BCS eligibility after NAC, and the regression model was used to develop the predicting nomogram. This nomogram was built using the training cohort (n=239) and was later validated with an independent validation cohort (n=123). Results: Small tumor size (p<0.001) at initial diagnosis, long distance from the nipple (p=0.002), high body mass index (p=0.001), and weak positivity for progesterone receptor (p=0.037) were found to be four independent predictors of an increased probability of BCS after NAC; further, these variables were used as covariates in developing the nomogram. For the training and validation cohorts, the areas under the receiver operating characteristic curve were 0.833 and 0.786, respectively; these values demonstrate the potential predictive power of this nomogram. Conclusion: This study established a new nomogram to predict successful BCS in patients with HR-positive, HER2-negative breast cancer. Given that chemotherapy is an option with unreliable outcomes for this subtype, this nomogram may be used to select patients for NAC followed by successful BCS.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• Journal of Korean Neurosurgical Society
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• v.64 no.5
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• pp.776-783
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• 2021

Objective : The purpose of this study was to identify risk factors for distal adding on (AO) or distal junctional kyphosis (DJK) in adolescent idiopathic scoliosis (AIS) treated by posterior spinal fusion (PSF) to L3 with a minimum 2-year follow-up. Methods : AIS patients undergoing PSF to L3 by two senior surgeons from 2000-2010 were analyzed. Distal AO and DJK were deemed poor radiographic results and defined as >3 cm of deviation from L3 to the center sacral vertical line (CSVL), or >10° angle at L3-4 on the posterior anterior- or lateral X-ray at ultimate follow-up. New stable vertebra (SV) and neutral vertebra (NV) scores were defined for this study. The total stability (TS) score was the sum of the SV and NV scores. Results : Ten of 76 patients (13.1%) were included in the poor radiographic outcome group. The other 66 patients were included in the good radiographic outcome group. Lower Risser grade, more SV-3 (CSVL doesn't touch the lowest instrumented vertebra [LIV]) on standing and side bending films, lesser NV and TS score, rigid L3-4 disc, more rotation and deviation of L3 were identified risk factors for AO or DJK. Age, number of fused vertebrae, curve correction, preoperative coronal/sagittal L3-4 disc angle did not differ significantly between the two groups. Multiple logistic regression results indicated that preoperative Risser grade 0, 1 (odds ratio [OR], 1.8), SV-3 at L3 in standing and side benders (OR, 2.1 and 2.8, respectively), TS score -5, -6 at L3 (OR, 4.4), rigid disc at L3-4 (OR, 3.1), LIV rotation >15° (OR, 2.9), and LIV deviation >2 cm from CSVL (OR, 2.2) were independent predictive factors. Although there was significant improvement of the of Scoliosis Research Society-22 average scores only in the good radiographic outcome group, there was no significant difference in the scores between the groups. Conclusion : The prevalence of AO or DJK at ultimate follow-up for AIS with LIV at L3 was 13.1%. To prevent AO or DJK following fusion to L3, we recommend that the CSVL touch L3 in both standing and side bending, TS score is -4 or less, the L3/4 disc is flexible, L3 is neutral (<15°) and ≤2 cm from the midline and the patient is ≥ Risser 2.