• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4467-4474
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• 2014

Background: We aimed to comprehensively review the evidence for using sputum DNA to detect non-small cell lung cancer (NSCLC). Materials and Methods: We searched PubMed, Science Direct, Web of Science, Chinese Biological Medicine (CBM), Chinese National Knowledge Infrastructure (CNKI), Wanfang, Vip Databases and Google Scholar from 2003 to 2013. The meta-analysis was carried out using a random-effect model with sensitivity, specificity, diagnostic odd ratios (DOR), summary receiver operating characteristic curves (ROC curves), area under the curve (AUC), and 95% confidence intervals (CI) as effect measurements. Results: There were twenty-two studies meeting the inclusion criteria for the meta-analysis. Combined sensitivity and specificity were 0.62 (95%CI: 0.59-0.65) and 0.73 (95%CI: 0.70-0.75), respectively. The DOR was 10.3 (95%CI: 5.88-18.1) and the AUC was 0.78. Conclusions: The overall accuracy of the test was currently not strong enough for the detection of NSCLC for clinical application. Dscovery and evaluation of additional biomarkers with improved sensitivity and specificity from studies rated high quality deserve further attention.

• Investigative Magnetic Resonance Imaging
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• v.22 no.1
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• pp.18-25
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• 2018

Purpose: To investigate the various imaging factors associated with aggravation of lumbar disc herniation (LDH) and develop a scoring system for prediction of LDH aggravation. Materials and Methods: From 2015 to 2017, we retrospectively reviewed the magnetic resonance imaging (MRI) findings of 60 patients (30 patients with aggravated LDH and 30 patients without any altered LDH). Imaging factors for MRI evaluation included the level of LDH, disc degeneration, back muscle atrophy, facet joint degeneration, ligamentum flavum thickness and interspinous ligament degeneration. Flexion-extension difference was measured with simple radiography. The scoring system was analyzed using receiver operating characteristic (ROC) analysis. Results: The aggravated group manifested a higher grade of disc degeneration, back muscle atrophy and facet degeneration than the control group. The ligamentum flavum thickness in the aggravated group was thicker than in the group with unaltered LDH. The summation score was defined as the sum of the grade of disc degeneration, back muscle atrophy and facet joint degeneration. The area under the ROC curve showing the threshold value of the summation score for prediction of aggravation of LDH was 0.832 and the threshold value corresponded to 6.5. Conclusion: Disc degeneration, facet degeneration, back muscle atrophy and ligamentum flavum thickness are important factors in predicting aggravation of LDH and may facilitate the determination of treatment strategy in patients with LDH. The summation score is available as supplemental data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.559-562
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• 2003

A motion-based background subtraction method without geometric computation is proposed, allowing that the camera is moving parallel to the ground plane with uniform velocity. The proposed method subtracts the background region from a given image by evaluating the difference between calculated and model Hows. This approach is insensitive to small errors of calculated optical flows. Furthermore, in order to tackle the significant errors, a strategy for incorporating a set of optical flows calculated over different frame intervals is presented. An experiment with two real image sequences, in which a static box or a moving toy car appears, to evaluate the performance in terms of accuracy under varying thresholds using a receiver operating characteristic (ROC) curve. The ROC curves show, in the best case, the figure-ground segmentation is done at 17.8 ％ in false positive fraction (FPF) and 71.3％ in true positive fraction (TPF) for the static-object scene and also at 14.8％ in FPF and 72.4％ In TPF for the moving-object scene, regardless if the calculated optical flows contain significant errors of calculation.

• Genomics & Informatics
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• v.14 no.4
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• pp.138-148
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• 2016

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the "large p and small n" problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

• Imaging Science in Dentistry
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• v.41 no.2
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• pp.53-57
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• 2011

Purpose : The purpose of this study was to evaluate the diagnostic performance of dental students in detection of mandibular condyle fractures and the effectiveness of reference panoramic images. Materials and Methods : Forty-six undergraduates evaluated 25 panoramic radiographs for condylar fractures and the data were analyzed through receiver operating characteristic (ROC) analysis. After a month, they were divided into two homogeneous groups based on the first results and re-evaluated the images with (group A) or without (group B) reference images. Eight reference images included indications showing either typical condylar fractures or anatomic structures which could be confused with fractures. Paired t-test was used for statistical analysis of the difference between the first and the second evaluations for each group, and student�fs t-test was used between the two groups in the second evaluation. The intra- and inter-observer agreements were evaluated with Kappa statistics. Results : Intra- and inter-observer agreements were substantial (k=0.66) and moderate (k=0.53), respectively. The area under the ROC curve (Az) in the first evaluation was 0.802. In the second evaluation, it was increased to 0.823 for group A and 0.814 for group B. The difference between the first and second evaluations for group A was statistically significant (p<0.05), however there was no statistically significant difference between the two groups in the second evaluation. Conclusion : Providing reference images to less experienced clinicians would be a good way to improve the diagnostic ability in detecting condylar fracture.

• Clinical and Experimental Pediatrics
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• v.61 no.1
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• pp.6-11
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• 2018

Purpose: Mid-upper-arm circumference (MUAC) is considered an alternative screening method for obesity. The aims of this investigation were to examine the ability of MUAC to correctly identify children with elevated body mass index (BMI) and to determine the best MUAC cutoff point for identification of children with high BMI. Methods: Anthropometric measurements (height, weight, and MUAC) from a cross-sectional sample of 7,921 Pakistani children aged 5-14 years were analyzed. Pearson correlation coefficients between MUAC and other anthropometric measurements were calculated. Receiver operating characteristic curve analysis was used to determine the optimal MUAC cutoff point for identifying children with high BMI. Results: Among 7,921 children, the mean (${\pm}$standard deviation) age, BMI, and MUAC were 10.00 (${\pm}2.86years$), 16.16 (${\pm}2.66kg/m^2$), and 17.73 (${\pm}2.59cm$), respectively. The MUAC had a strong positive correlation with BMI. The optimal MUAC cutoff points indicating elevated BMI in boys ranged from 16.76 to 22.73, while the corresponding values in girls ranged from 16.38 to 20.57. Conclusion: MUAC may be used as a simple indicator of overweight/obesity in children, with reasonable accuracy in clinical settings.

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.176-183
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• 2005

The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

• Ocean Systems Engineering
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• v.6 no.3
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• pp.217-231
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• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6919-6922
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• 2014

Background: The cytological analysis of serous effusions is a common investigation and yields important diagnostic information. However, the distinction of reactive mesothelial cells from malignant cells can sometimes be difficult for the cytopathologist. Hence cost-effective ancillary methods are essential to enhance the accuracy of cytological diagnosis. The aim of this study was to examine the utility of nuclear morphometry in differentiating reactive mesothelial cells from malignant cells in effusion smears. Materials and Methods: Sixty effusion smears consisting of 30 effusions cytologically classified as malignant (adenocarcinomas) and 30 benign effusions showing reactive mesothelial cells were included in the study. ImageJ was used to measure the nuclear area, perimeter, maximal feret diameter, minimal feret diameter and the circularity. A total of ten representative cells were studied in each case. Results: Significant differences were found between benign and malignant effusions for the nuclear area, perimeter, maximal feret diameter and minimal feret diameter. No significant difference was found for circularity, a shape descriptor. Receiver operating characteristic (ROC) curve analysis revealed that nuclear area, perimeter, maximal feret diameter, and minimal feret diameter are helpful in discriminating benign and malignant effusions. Conclusions: Computerised nuclear morphometry is a helpful ancillary technique to distinguish benign and malignant effusions. ImageJ is an excellent cost effective tool with potential diagnostic utility in effusion cytology.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7133-7136
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• 2013

Background: We studied Surveillance, Epidemiology and End Results (SEER) breast cancer data of Georgia USA to analyze the impact of socio-economic factors on the disparity of breast cancer treatment outcome. Materials and Methods: This study explored socio-economic, staging and treatment factors that were available in the SEER database for breast cancer from Georgia registry diagnosed in 2004-2009. An area under the receiver operating characteristic curve (ROC) was computed for each predictor to measure its discriminatory power. The best biological predictors were selected to be analyzed with socio-economic factors. Survival analysis, Kolmogorov-Smirnov 2-sample tests and Cox proportional hazard modeling were used for univariate and multivariate analyses of time to breast cancer specific survival data. Results: There were 34,671 patients included in this study, 99.3% being females with breast cancer. This study identified race and education attainment of county of residence as predictors of poor outcome. On multivariate analysis, these socio-economic factors remained independently prognostic. Overall, race and education status of the place of residence predicted up to 10% decrease in cause specific survival at 5 years. Conclusions: Socio-economic factors are important determinants of breast cancer outcome and ensuring access to breast cancer treatment may eliminate disparities.