• Journal of Chest Surgery
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• v.46 no.6
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• pp.433-438
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• 2013

Background: Surgical repair of post-infarct ventricular septal defect (VSD) is considered one of the most challenging procedures having high surgical mortality. This study aimed to evaluate the outcomes of the surgical repair of post-infarct VSD. Methods: From May 1991 to July 2012, 34 patients (mean age, $67.1{\pm}7.9$ years) underwent surgical repair of post-infarct VSD. A retrospective review of clinical and surgical data was performed. Results: VSD repair involved the infarct exclusion technique using a patch in all patients. For coronary revascularization, 12 patients (35.3%) underwent concomitant coronary artery bypass graft, 3 patients (8.8%) underwent preoperative percutaneous coronary intervention, and 9 patients (26.5%) underwent both of these procedures. The early mortality rate was 20.6%. Six patients (17.6%) required reoperation due to residual shunt or newly developed VSD. During follow-up (median, 4.8 years; range, 0 to 18.4 years), late death occurred in nine patients. Overall, the 5-year and 10-year survival rates were $54.4%{\pm}8.8%$ and $44.3%{\pm}8.9%$, respectively. According to a Cox regression analysis, preoperative cardiogenic shock (p=0.069) and prolonged cardiopulmonary bypass time (p=0.008) were independent predictors of mortality. Conclusion: The early surgical outcome of post-infarct VSD was acceptable considering the high-risk nature of the disease. The long-term outcome, however, was still dismal, necessitating comprehensive optimal management through close follow-up.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.199-208
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• 2017

This study investigated the effects of overtime work on the health-related quality of life (HRQoL) of Korean blue-collar workers. This cross-sectional study collected data on 229 Korean blue-collar workers in six small-sized companies from October to November 2015. The data were analyzed using hierarchical multiple regression analysis to estimate the effect of overtime work while considering convergence variables. In the hierarchical regression model, when overtime work variable was included in the model, $R^2$ change was statistically significant. The significant predictors for HRQoL were overtime work (${\beta}=.152$, p=.025), depression (${\beta}=-.192$, p=.003) and night shift work (${\beta}=-.201$, p=.032). The results of this study provide a basic data for establishing optimal working hours standards for improving the quality of life of Korean blue-collar workers.

• Horticultural Science & Technology
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• v.33 no.6
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• pp.845-853
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• 2015

The objective of this study was to predict the timing of nitrogen (N) demand through analyzing chlorophyll fluorescence (ChlF), soil-plant analysis development (SPAD), and normalized difference vegetation index (NDVI), which are positively correlated with foliar N concentration in star cluster (Pentas lanceolata). The plants were grown in potting soil under optimal conditions for 30 d, followed by weekly irrigation with five concentrations (0, 4, 8, 16, and 24 mM) of N for an additional 30 d. These five N application levels corresponded to leaf N concentrations of 2.62, 3.48, 4.00, 4.23, and 4.69%, respectively. We measured 13 morphological and physiological parameters, as well as the responses of these parameters to various N-fertilizer treatments. The general increases in Dickson's quality index (DQI), above-ground dry weight (DW), total DW, flowering rate, ${\Delta}F/Fm$', and qP in response to treatment with 0 to 8 mM N were similar to those of SPAD, NDVI, and Fv/Fm. Consistent and strong correlations ($R^2$= 0.60 to 0.85) were observed between leaf N concentration (%) and SPAD, NDVI, ${\Delta}F/Fm$', and above-ground DW. Validation of leaf S PAD, NDVI, and ${\Delta}F/Fm$' revealed that these vegetation indices are accurate predictors of leaf N concentration that can be used for non-destructive estimation of the proper timing for N-solution irrigation of P. lanceolata. Moreover, irrigation with 8 mM N-fertilizer i s recommended w hen leaf N concentration, SPAD, NVDI, and ${\Delta}F/Fm$' ratios are reduced from their saturation values of 4.00, 50.68, 0.64, and 0.137%, respectively.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7463-7466
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• 2015

Aims: To analyse the predictors of recurrence, disease free survival and overall survival in cases with endometrial cancer. Materials and Methods: A total of 152 women diagnosed with endometrial cancer were screened using a prospectively collected database including age, smoking history, menopausal status, body mass index, CA125, systemic disorders, tumor histology, tumor grade, lymphovascular space invasion, tumor diameter, cervical involvement, myometrial invasion, adnexal metastases, positive cytology, serosal involvement, other pelvic metastases, type of surgery, fertility sparing approach to assess their ability to predict recurrence, disease free survival and overall survival. Results: In ROC analyses tumor diameter was a significant predictor of recurrence (AUC:0.771, P<0.001). The optimal cut off value was 3.75 with 82% sensitivity and 63% specificity. In correlation analyses tumor grade (r=0.267, p=0.001), tumor diameter (r=0.297, p<0.001) and the serosal involvement (r=0.464, p<0.001) were found to significantly correlate with the recurrence. In Cox regression analyses when some different combinations of variables included in the model which are found to be significantly associated with the presence of recurrence, tumor diameter was found to be a significant confounder for disease free survival (OR=1.2(95 CI,1.016-1.394, P=0.031). On Cox regression for overall survival only serosal involvement was found to be a significant predictor (OR=20.8 (95 % CI 2.4-179.2, P=0.006). In univariate analysis of tumor diameter > 3.75 cm and the recurrence, there was 14 (21.9 %) cases with recurrence in group with high tumor diameter where as only 3 (3.4 %) cases group with smaller tumor size (Odds ratio:7.9 (95 %CI 2.2-28.9, p<0.001). Conclusions: Although most of the significantly correlated variables are part of the FIGO staging, tumor diameter was also found to be predictor for recurrence with higher values than generally accepted.

• The Journal of the Acoustical Society of Korea
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• v.31 no.2
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• pp.93-99
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• 2012

For speech coding, a vocal tract is modeled using Linear Predictive Coding (LPC) coefficients. The LPC coefficients are typically transformed to Line Spectral Frequency (LSF) parameters which are advantageous for linear interpolation and quantization. If multidimensional LSF data are quantized directly using Vector-Quantization (VQ), high rate-distortion performance can be obtained by fully utilizing intra-frame correlation. In practice, since this direct VQ system cannot be used due to high computational complexity and memory requirement, Split VQ (SVQ) is used where a multidimensional vector is split into multilple sub-vectors for quantization. The LSF parameters also have high inter-frame correlation, and thus Predictive SVQ (PSVQ) is utilized. PSVQ provides better rate-distortion performance than SVQ. In this paper, to implement the optimal predictors in PSVQ for voice storage devices, we propose Multi-Frame AR-model based SVQ (MF-AR-SVQ) that considers the inter-frame correlations with multiple previous frames. Compared with conventional PSVQ, the proposed MF-AR-SVQ provides 1 bit gain in terms of spectral distortion without significant increase in complexity and memory requirement.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.1
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• pp.381-385
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• 2015

Background:Hepatocellular carcinoma (HCC) is the second most common malignancy in Egypt. Data mining is a method of predictive analysis which can explore tremendous volumes of information to discover hidden patterns and relationships. Our aim here was to develop a non-invasive algorithm for prediction of HCC. Such an algorithm should be economical, reliable, easy to apply and acceptable by domain experts. Methods: This cross-sectional study enrolled 315 patients with hepatitis C virus (HCV) related chronic liver disease (CLD); 135 HCC, 116 cirrhotic patients without HCC and 64 patients with chronic hepatitis C. Using data mining analysis, we constructed a decision tree learning algorithm to predict HCC. Results: The decision tree algorithm was able to predict HCC with recall (sensitivity) of 83.5% and precession (specificity) of 83.3% using only routine data. The correctly classified instances were 259 (82.2%), and the incorrectly classified instances were 56 (17.8%). Out of 29 attributes, serum alpha fetoprotein (AFP), with an optimal cutoff value of ${\geq}50.3ng/ml$ was selected as the best predictor of HCC. To a lesser extent, male sex, presence of cirrhosis, AST>64U/L, and ascites were variables associated with HCC. Conclusion: Data mining analysis allows discovery of hidden patterns and enables the development of models to predict HCC, utilizing routine data as an alternative to CT and liver biopsy. This study has highlighted a new cutoff for AFP (${\geq}50.3ng/ml$). Presence of a score of >2 risk variables (out of 5) can successfully predict HCC with a sensitivity of 96% and specificity of 82%.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.15
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• pp.6263-6267
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• 2014

Background: It is standard treatment to combine chemotherapy (CT) and thoracic radiotherapy (TRT) in treating patients with limited stage small cell lung cancer (LS-SCLC). However, optimal timing of TRT is unclear. We here evaluated the survival impact of early versus late TRT in patients with LS-SCLC. Materials and Methods: Follow-up was retrospectively analyzed for seventy consecutive LS-SCLC patients who had successfully completed chemo-TRT between January 2006 and January 2012. Patients received TRT after either 1 to 2 cycles of CT (early TRT) or after 3 to 6 cycles of CT (late TRT). Survival and response rates were evaluated using the Kaplan-Meier method and comparisons were made using the multivariate Cox regression test. Results: Median follow-up was 24 (5 to 57) months. Carboplatin+etoposide was the most frequent induction CT (59%). Median overall, disease free, and metastasis free survivals in all patients were 15 (5 to 57), 5 (0 to 48) and 11 (3 to 57) months respectively. Late TRT was superior to early TRT group in terms of response rate (p=0.05). 3 year overall survival (OS) rates in late versus early TRT groups were 31% versus 17%, respectively (p=0.03). Early TRT (p=0.03), and incomplete response to TRT (p=0.004) were negative predictors of OS. Significant positive prognostic factors for distant metastasis free survival were late TRT (p=0.03), and use of PCI (p=0.01). Use of carboplatin versus cisplatin for induction CT had no significant impact on OS (p=0.634), DFS (p=0.727), and MFS (p=0.309). Conclusions: Late TRT appeared to be superior to early TRT in LS-SCLC treatment in terms of complete response, OS and DMFS. Carboplatin or cisplatin can be combined with etoposide in the induction CT owing to similar survival outcomes.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.4
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• pp.1435-1442
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• 2015

Purpose: To study the patient load, treatment pattern, survival outcome and its predictors in patients with brain metastases treated by radiotherapy. Materials and Methods: Data for patients with brain metastases treated by radiotherapy between 2003 and 2007 were collected from medical records, the hospital information system database, and a population-based tumor registry database until death or at least 5 years after treatment and retrospectively reviewed. Results: The number of treatments for brain metastases gradually increased from 48 in 2003 to 107 in 2007, with more than 70% from lung and breast cancers. The majority were treated with whole brain radiation of 30 Gy (3 Gy X 10 fractions) by cobalt-60 machine, using radiation alone. The overall median survival of the 418 patients was 3.9 months. Cohort analysis of relative survival after radiotherapy was as follows: 52% at 3 months, 18% at 1 year and 3% at 5 years in males; and 66% at 3 months, 26% at 1 year and 7% at 5 years in females. Multivariate analysis demonstrated that the patients treated with combined modalities had a better prognosis. Poor prognostic factors included primary cancer from the lung or gastrointestinal tract, emergency or urgent consultation, poor performance status (ECOG 3-4), and a hemoglobin level before treatment of less than 10 g/dl. Conclusions: This study identified an increasing trend of patient load with brain metastases. Possible over-treatment and under-treatment were demonstrated with a wide range of survival results. Practical prognostic scoring systems to assist in decision-making for optimal treatment of different patient groups is absolutely necessary; it is a key strategy for balancing good quality of care and patient load.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.127-134
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• 2007

There are many researches about the intelligent stock trading systems with the help of the advance of the artificial intelligence such as machine learning techniques, Though the establishment of the reasonable trading policy plays an important role in the performance of the trading systems most researches focused on the improvement of the predictability. Also some previous works, which treated the trading policy, treated the simplified versions dependent on the predictors in less systematic ways. In this paper, we propose the integrated multiple simulation' as a method of optimizing trading performance of stock trading systems. The propose method is adopted in the NXShell a development environment for neural network based stock trading systems. Under the proposed integrated multiple simulation', we simulate the multiple tradings for all combinations of the neural network's outputs and the trading policy parameters, evaluate the learning performance according to the various metrics and establish the optimal policy for a given prediction module based on the resulting performance. In the experiment, we present the trading policy comparison results using the stock value data from the KOSPI and KOSDAQ.

• Radiation Oncology Journal
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• v.31 no.3
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• pp.111-117
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• 2013

Purpose: To determine whether the maximum standardized uptake value (SUV) of [$^{18}F$] fluorodeoxyglucose uptake by positron emission tomography (FDG PET) ratio of lymph node to primary tumor (mSUVR) could be a prognostic factor for node positive non-small cell lung cancer (NSCLC) patients treated with definitive radiotherapy (RT). Materials and Methods: A total of 68 NSCLC T1-4, N1-3, M0 patients underwent FDG PET before RT. Optimal cutoff values of mSUVR were chosen based on overall survival (OS). Independent prognosticators were identified by Cox regression analysis. Results: The most significant cutoff value for mSUVR was 0.9 with respect to OS. Two-year OS was 17% for patients with mSUVR > 0.9 and 49% for those with mSUVR ${\leq}0.9$ (p = 0.01). In a multivariate analysis, including age, performance status, stage, use of chemotherapy, and mSUVR, only performance status (p = 0.05) and mSUVR > 0.9 (p = 0.05) were significant predictors of OS. Two-year OS for patients with both good performance (Eastern Cooperative Oncology Group [ECOG] ${\leq}1$) and mSUVR ${\leq}0.9$ was significantly better than that for patients with either poor performance (ECOG > 1) or mSUVR > 0.9, 23% (71% vs. 23%, p = 0.04). Conclusion: Our results suggested that the mSUVR was a strong prognostic factor among patients with lymph node positive NSCLC following RT. Addition of mSUVR to performance status identifies a subgroup at highest risk for death after RT.