• Journal of Yeungnam Medical Science
• /
• v.33 no.1
• /
• pp.8-12
• /
• 2016

Background: The decision to administer oral anticoagulation therapy depends on accurate assessment of stroke risk in patients with atrial fibrillation (AF). Various stroke risk stratification schemes have been developed to help inform clinical decision making. The CHADS2 and CHA2DS2-VASc scores have been used in estimating the risk of stroke in patients with AF. Recently R2CHA2DS2-VASc score was developed. The objective of the current study is to validate the usefulness of the R2CHA2DS2-VASc score and to compare the accuracy of the CHADS2, CHA2DS2-VASc, and R2CHA2DS2-VASc scores in predicting a patient's risk of stroke. Methods: Based on medical records, we conducted a retrospective study of patients hospitalized with AF from March 2011 to July 2013. A total of 448 AF patients were included in this study. The receiver operating characteristic (ROC) curve analysis in MedCalc was used for comparison with respective diagnostic values. Results: The patient characteristics showed male predominance (60.9%). Among the 448 AF patients, 131 (29.2%) patients had strokes during the study. A R2CHA2DS2-VASc score of more than 5 is the optimal cut-off value for prediction of stroke. A risk score of three, the area under the ROC curve (AUC) of R2CHA2DS2-VASc score (AUC 0.631; 95% confidence interval, 0.585-0.679) was the highest. A significant difference was observed between AUC for R2CHA2DS2-VASc, CHADS2, and CHA2DS2-VASc scores, but no meaningful difference between CHADS2 and CHA2DS2-VASc scores. Conclusion: We determined the usefulness of the R2CHA2DS2-VASc score, which showed better association with stroke than the CHADS2 and CHA2DS2-VASc scores.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.4
• /
• pp.1-11
• /
• 2019

With the development of remote sensing sensor technology, it has become possible to acquire satellite images with various spectral information. In particular, since the hyperspectral image is composed of continuous and narrow spectral wavelength, it can be effectively used in various fields such as land cover classification, target detection, and environment monitoring. Change detection techniques using remote sensing data are generally performed through differences of data with same dimensions. Therefore, it has a disadvantage that it is difficult to apply to heterogeneous sensors having different dimensions. In this study, we have developed a change detection method applicable to hyperspectral image and high spat ial resolution satellite image with different dimensions, and confirmed the applicability of the change detection method between heterogeneous images. For the application of the change detection method, the dimension of hyperspectral image was reduced by using correlation analysis and principal component analysis, and the change detection algorithm used CVA. The ROC curve and the AUC were calculated using the reference data for the evaluation of change detection performance. Experimental results show that the change detection performance is higher when using the image generated by adequate dimensionality reduction than the case using the original hyperspectral image.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.3
• /
• pp.19-34
• /
• 2018

The purpose of this study is to estimate monthly agricultural reservoir storage with multiple linear regression model(MLRM) based on reservoir storage and meteorological data. The regression model was developed using 15 years(2002 to 2016) of 3,067 reservoirs by KRC(Korea Rural Community) and 63 meteorological stations by KMA (Korean Meteorological Administration), and the MLRM showed the determination coefficient($R^2$) of 0.51~0.95. The MLRM was applied to 9 selected reservoirs among the whole reservoirs and validated with $R^2$ of 0.44~0.81. The ROC(Receiver Operating Characteristics) analysis of Reservoir Drought Index(RDI) classified by comparing the present reservoir storage with normal year(1976~2005 average) reservoir storage showed average value of 0.64 for 2 years(2015~2016) with the highest value of 0.70 for winter period, lowest value of 0.58 for summer period. If 1 to 3 months weather forecasting data such as Glosea5 produced by KMA are applied, the predicted monthly reservoir storage from the MLRM can be a useful information for agricultural drought pre-preparation.

• Journal of the Korean Society of Industry Convergence
• /
• v.24 no.6_2
• /
• pp.729-735
• /
• 2021

Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.

• Nutrition Research and Practice
• /
• v.16 no.5
• /
• pp.604-615
• /
• 2022

BACKGROUND/OBJECTIVES: This study aimed to investigate cancer-specific survival (CSS) and associated risk factors in elderly gastric cancer (EGC) patients. SUBJECTS/METHODS: EGC patients (≥ 70 yrs) who underwent curative gastrectomy between January 2013 and December 2017 at our hospital were included. Clinicopathologic characteristics and survival data were collected. Receiver operating characteristic (ROC) analysis was used to extract the best cutoff point for body mass index (BMI). A Cox proportional hazards model was used to determine the risk factors for CSS. RESULTS: In total, 290 EGC patients were included, with a median age of 74.7 yrs. The median follow-up time was 31 (1-77) mon. The postoperative 1-yr, 3-yr and 5-yr CSS rates were 93.7%, 75.9% and 65.1%, respectively. Univariate analysis revealed risk factors for CSS, including age (hazard ratio [HR] = 1.08; 95% confidence interval [CI], 1.01-1.15), intensive care unit (ICU) admission (HR = 1.73; 95% CI, 1.08-2.79), nutritional risk screening (NRS 2002) score ≥ 5 (HR = 2.33; 95% CI, 1.49-3.75), and preoperative prognostic nutrition index score < 45 (HR = 2.06; 95% CI, 1.27-3.33). The ROC curve showed that the best BMI cutoff value was 20.6 kg/m². Multivariate analysis indicated that a BMI ≤ 20.6 kg/m² (HR = 2.30; 95% CI, 1.36-3.87), ICU admission (HR = 1.97; 95% CI, 1.17-3.30) and TNM stage (stage II: HR = 5.56; 95% CI, 1.59-19.43; stage III: HR = 16.20; 95% CI, 4.99-52.59) were significantly associated with CSS. CONCLUSIONS: Low BMI (≤ 20.6 kg/m²), ICU admission and advanced pathological TNM stages (II and III) are independent risk factors for CSS in EGC patients after curative gastrectomy. Nutrition support, better perioperative management and early diagnosis would be helpful for better survival.

• Korean Journal of Radiology
• /
• v.22 no.5
• /
• pp.770-781
• /
• 2021

Objective: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. Materials and Methods: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTR_asym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. Results: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTR_asym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTR_asym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. Conclusion: CEST MRI potentially allows noninvasive image alterations in the Alzheimer's disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.

• Laboratory Medicine Online
• /
• v.6 no.1
• /
• pp.25-30
• /
• 2016

Background: The cell cycle-dependent enzyme thymidine kinase 1 (TK1) is known to increase during cancer cell proliferation and has been reported as a prognostic marker for various hematologic malignancies and solid tumors. This study aimed to determine the reference interval in Korean healthy controls and to evaluate the usefulness of TK1 as a biomarker for aggressive clinical behavior in B-cell lymphoma patients. Methods: We enrolled 72 previously untreated patients with B-cell lymphoma and 143 healthy controls. Serum TK1 levels were measured by chemiluminescence immunoassay ($Liaison^{(R)}$, DiaSorin, USA). We established the reference intervals in healthy controls. The diagnostic performance of serum TK1 was studied using receiver operating characteristic (ROC) analysis, and the correlation between the cutoff level for serum TK1 and clinical characteristics of B-cell lymphoma was evaluated. Results: The reference range (95th percentile) of serum TK1 in healthy controls was 5.4-21.8 U/L. There was a clear difference in TK1 levels between patients with B-cell lymphoma and healthy controls ($40.6{\pm}68.5$ vs. $11.8{\pm}4.4U/L$, P <0.001). The area under the curve of serum TK1 for the diagnosis of B-cell lymphoma was 0.73 (cutoff, 15.2 U/L; sensitivity, 59.7%; specificity, 83.2%). An increased TK1 level (${\geq}15.2U/L$) correlated with the advanced clinical stage (P <0.001), bone marrow involvement (P =0.013), international prognostic index score (P =0.001), lactate dehydrogenase level (P =0.001), low Hb level (<12 g/dL) (P =0.028), and lymphocyte count (P =0.023). Conclusions: The serum TK1 level could serve as a useful biomarker for aggressive clinical behavior in B-cell lymphoma patients.

• Journal of Chest Surgery
• /
• v.41 no.1
• /
• pp.55-60
• /
• 2008

Background: Circulating levels of brain natriuretic peptide (BNP) provide prognostic information for patients with heart failure. The aim of our study was to investigate whether preoperative and postoperative BNP levels could predict postoperative complications and outcomes in patients after coronary artery bypass graft (CABG). Material and Method: Data was collected prospectively on 30 patients (M/F=19/11, age $60.0{\pm}9.6$ years) undergoing conventional CABG during a 1-year period beginning on January 1, 2005. Patients underwent off-pump CABG, and combined surgery was excluded. The BNP assay was performed preoperatively, immediate postoperatively at the intensive care unit (ICU), and 1, 3, 5, and 7days postoperatively. Result: Preoperative BNP levels significantly correlated with preoperative echocardiographic ejection fraction and an ICU stay of 5 days or more (r=-0.4, p=0.028; r=0.39, p=0.031, respectively). A preoperative BNP cut-off value above 263 pg/mL demonstrated high specificity (90.5%) for predicting postoperative complications using the receiver operating characteristics curves. Preoperative and postoperative (7 days) BNP levels were different depending on the abscence (mean BNP=$99{\pm}23\;pg/mL$ vs. $296{\pm}74\;pg/mL$, p<0.05) and presence (mean BNP=$212{\pm}29\;pg/mL$ vs. $408{\pm}23\;pg/mL$, p<0.01). Conclusion: Preoperative BNP levels >263 pg/mL predict postoperative complications in patients receiving CABG.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.11
• /
• pp.4629-4635
• /
• 2014

Background: Diffusion-weighted imaging (DWI) makes it possible to detect malignant tumors based on the diffusion of water molecules. However, it is uncertain whether DWI has advantages over FDG-PET for distinguishing malignant from benign pulmonary nodules and masses. Materials and Methods: One hundred-forty-three lung cancers, 17 metastatic lung tumors, and 29 benign pulmonary nodules and masses were assessed in this study. DWI and FDG-PET were performed. Results: The apparent diffusion coefficient (ADC) value ($1.27{\pm}0.35{\times}10^{-3}mm^2/sec$) of malignant pulmonary nodules and masses was significantly lower than that ($1.66{\pm}0.58{\times}10^{-3}mm^2/sec$) of benign pulmonary nodules and masses. The maximum standardized uptake value (SUVmax: $7.47{\pm}6.10$) of malignant pulmonary nodules and masses were also significantly higher than that ($3.89{\pm}4.04$) of benign nodules and masses. By using optimal cutoff values for ADC ($1.44{\times}10^{-3}mm^2/sec$) and for SUVmax (3.43), which were determined with receiver operating characteristics curves (ROC curves), the sensitivity (80.0%) of DWI was significantly higher than that (70.0%) of FDG-PET. The specificity (65.5%) of DWI was equal to that (65.5%) of FDG-PET. The accuracy (77.8%) of DWI was not significantly higher than that (69.3%) of FDG-PET for pulmonary nodules and masses. As the percentage of bronchioloalveolar carcinoma (BAC) component in adenocarcinoma increased, the sensitivity of FDG-PET decreased. DWI could not help in the diagnosis of mucinous adenocarcinomas as malignant, and FDG-PET could help in the correct diagnosis of 5 out of 6 mucinous adenocarcinomas as malignant. Conclusions: DWI has higher potential than PET in assessing pulmonary nodules and masses. Both diagnostic approaches have their specific strengths and weaknesses which are determined by the underlying pathology of pulmonary nodules and masses.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.16
• /
• pp.6805-6810
• /
• 2014

Background: Previous studies have suggested a link between obesity and breast cancer (BC). However, there is no universal consensus, especially in population based studies. Because only few studies have been conducted on African women, we aimed here to assess the relationship between BMI at time of diagnosis and the BC histopathological features among Tunisian patients according to menopausal status using a hospital-based prospective cohort study. Materials and Methods: Clinical and pathological data were collected from 262 patients stratified on four groups according to their BMI. The relationship between BMI and histopathological features at diagnosis was analysed using univariate and multivariate analysis. Receiver-operating characteristic (ROC) curves were used to evaluate the performance of BMI in predicting of high tumor grade, in comparison to ki-67 index of proliferation. Results: Obesity was correlated with larger tumors, advanced grade and with ER-PR-Her2+ BC subtype. An association of BMI with tumor size and tumor grade was observed in both premenopausal and postmenopausal women. Additionally, a significant association between BMI and ER+, ER+PR+Her2+ and ER-PR-Her2+ status was revealed for premenopausal patients, while only ER+PR+Her2+ was associated with BMI for postmenopausal women. Finally, our results showed that compared to Ki67 proliferation index, BMI is a useful prognostic marker of high grade BC tumors. Conclusions: These data are the first to show that in Tunisia obese women suffering from BC have significantly larger tumors and advanced tumor grade and that higher BMI might influence tumor characteristics and behavior.