• Journal of the Korean Society of Physical Medicine
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• v.9 no.3
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• pp.301-305
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• 2014

PURPOSE: The purpose of this study was to determine the optimal thresholds of serum lipid level related to hypertension according to age in Korean adults. METHODS: In total, 564 adults who visited the health examine center in general hospital were included. The blood pressure and lipid profiles of low density lipoprotein cholesterol(LDL), high density lipoprotein cholesterol (HDL), triglyceride(TG) were measured. Receiver operating characteristic (ROC) curve were used to establish optimal thresholds between blood pressure and lipid profiles. RESULTS: The optimal TG cutoff value were 110.50(mg/dl) in the 18-39 and 81.50(mg/dl) in the 40-59 age group, and optimal cutoff value of LDL were 126.50(mg/dl) in the 40-59 age group and 111.00(mg/dl) in the 60 and over age group. There was a negative correlation between HDL and hypertension, a higher HDL decreased hypertension. The optimal cutoff value of HDL was 49.50(mg/dl) in the 18-39 age group. CONCLUSION: The thresholds of hypertension were lower in LDL and TG with aging. This result indicated that elderly people needs to concern more about their lipid profiles to maintain healthy cardiovascular function.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.347-352
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• 2016

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Conclusions: Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

• ETRI Journal
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• v.41 no.6
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• pp.797-810
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• 2019

Image saliency detection is the basis of perceptual image processing, which is significant to subsequent image processing methods. Most saliency detection methods can detect only a single object with a high-contrast background, but they have no effect on the extraction of a salient object from images with complex low-contrast backgrounds. With the prior knowledge, this paper proposes a method for detecting salient objects by combining the boundary contrast map and the geodesics-like maps. This method can highlight the foreground uniformly and extract the salient objects efficiently in images with low-contrast backgrounds. The classical receiver operating characteristics (ROC) curve, which compares the salient map with the ground truth map, does not reflect the human perception. An ROC curve with distance (distance receiver operating characteristic, DROC) is proposed in this paper, which takes the ROC curve closer to the human subjective perception. Experiments on three benchmark datasets and three low-contrast image datasets, with four evaluation methods including DROC, show that on comparing the eight state-of-the-art approaches, the proposed approach performs well.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.107-117
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• 2022

Purpose : The purpose of this study was to establish a model of the predictive factors for success or failure of examinees undertaking the Korean physical therapist licensing examination (KPTLE). Additionally, we assessed the pass/fail cut-off point. Methods : We analyzed the results of 10,881 examinees who undertook the KPTLE, using data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was the test result (pass or fail), and the input variables were: sex, age, test subject, and total score. Frequency analysis, chi-square test, descriptive statistics, independent t-test, correlation analysis, binary logistic regression, and receiver operating characteristic (ROC) curve analyses were performed on the data. Results : Sex and age were not significant predictors of attaining a pass (p>.05). The test subjects with the highest probability of passing were, in order, medical regulation (MR) (Odds ratio (OR)=2.91, p<.001), foundations of physical therapy (FPT) (OR=2.86, p<.001), diagnosis and evaluation for physical therapy (DEPT) (OR=2.74, p<.001), physical therapy intervention (PTI) (OR=2.66, p<.001), and practical examination (PE) (OR=1.24, p<.001). The cut-off points for each subject were: FPT, 32.50; DEPT, 29.50; PTI, 44.50; MR, 14.50; and PE, 50.50. The total score (TS) was 164.50. The sensitivity, specificity, and the classification accuracy of the prediction model was 99 %, 98 %, and 99 %, respectively, indicating high accuracy. Area under the curve (AUC) values for each subject were: FPT, .958; DEPT, .968; PTI, .984; MR, .885; PE, .962; and TS, .998, indicating a high degree of fit. Conclusion : In our study, the predictive factors for passing KPTLE were identified, and the optimal cut-off point was calculated for each subject. Logistic regression was adequate to explain the predictive model. These results will provide universities and examinees with useful information for predicting their success or failure in the KPTLE.

• Imaging Science in Dentistry
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• v.30 no.3
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• pp.155-158
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• 2000

The purpose of this paper is to explain the making procedure and the usage of receiver operating characteristic (ROC) curve for interpretation of radiographic images. The conventional radiograms obtained after the creation of the lesions in the acrylic plates and were enhanced in color. The observer were informed of which tooth to examine, the 'a priori' probability of a lesion present and the approximate diameter of the lesions. The two groups of films were interpreted separately by the same observer using the same rating scale. The following rating scale was used: A; definitely no lesion, B; probably no lesion, C; not sure, D; probably a lesion, and E; definitely a lesion. In analysis, for each observer the diagnostic results in terms of true positive (TP) and false positive (FP) decisions were plotted on a graph. The lowest point on the graph represents the TP and FP when only decisions designated as E according to the rating scale are included. The next point shows the TP and FP values when diagnoses designated as D are added and so forth. By connecting such plot points, a receiver operating characteristic (ROC) curves is obtained. The area under the curve represents the diagnostic accuracy resulting from a diagnostic performance at pure chance level and a value of 1.0 at perfect performance. This method has been known as an useful method to detect the minute difference for each radiographic technic, each observer and for the different lesion depths.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.533-545
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• 2022

Collection of data on several variables, especially in the field of medicine, results in the problem of measurement errors. The presence of such measurement errors may influence the outcomes or estimates of the parameter in the model. In classification scenario, the presence of measurement errors will affect the intrinsic cum summary measures of Receiver Operating Characteristic (ROC) curve. In the context of ROC curve, only a few researchers have attempted to study the problem of measurement errors in estimating the area under their respective ROC curves in the framework of univariate setup. In this paper, we work on the estimation of area under the multivariate ROC curve in the presence of measurement errors. The proposed work is supported with a real dataset and simulation studies. Results show that the proposed bias-corrected estimator helps in correcting the AUC with minimum bias and minimum mean square error.

• Physical Therapy Korea
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• v.25 no.1
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• pp.39-46
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• 2018

Background: The Berg Balance Scale (BBS) and the Fullerton Advanced Balance (FAB) scale have been used to assess balance function in patients with chronic stroke. These clinical balance scales provide information about potential risk factors for falls. Objects: The purpose of this study was to investigate the incidence of and risk factors of falls and compare the predictive values of the BBS and FAB scale relative to fall risk in patients with stroke through receiver operating characteristic analysis. Methods: Sixty-three patients with stroke (faller=34, non-faller=29) who could walk independently for 10 meters participated in this study. The BBS and FAB scale were administered. Then, we verified the cut-off score, sensitivity, specificity, and the area of under the curve. Results: In this study, the BBS and FAB scale did not predict fall risk in patients with stroke in the receiver operator characteristic curve analysis. A cut-off score of 37.5 points provided sensitivity of .47 and specificity of .35 on the BBS, and a cut-off score of 20.5 points provided sensitivity of .44 and specificity of .45 on the FAB scale. Conclusion: The BBS and FAB scale were not useful screening tools for predicting fall risk in patients with stroke in this study, but those who scored 37.5 or lower on the BBS and 20.5 or lower on the FAB scale had a high risk for falls.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.146-155
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• 2020

This study was to evaluate the usefulness of gamma glutamyl transferase (GGT) as a surrogate marker predicting metabolic syndrome. 7,155 non obese men over the age of 20 were studied as subjects. The criteria for diagnosing MetS were the National Cholesterol Education Program - Third Adult Treatment Panel (NCEP-ATP III). The risk of developing MetS according to GGT was conducted logistic regression analysis, and the ROC (receiver operating characteristic) curve was obtained to confirm GGT ability to predict the risk of MetS. Regardless of age and body mass index, MetS had a 7.09 times higher risk of onset in the fourth quartile than in the first quartile of GGT (p<0.001). The AUC (area under the curve) of GGT for the diagnosis of MetS was 0.715, and the cutoff value of GGT was 40.0 U/L, the sensitivity was 65.0%, and the specificity was 70.2%. Therefore, GGT is considered to be a useful diagnostic index for diagnosing MetS.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.199-209
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• 2022

Typical anomaly detection algorithms are trained by using prior data. Thus the batch learning based algorithms cause inevitable performance degradation when characteristics of newly incoming normal data change over time. We propose an online anomaly detection algorithm which can consider the gradual characteristic changes of incoming normal data. The proposed algorithm based on one-class classification model includes both offline and online learning procedures. In offline learning procedure, the algorithm learns the prior data to be close to centroid of the latent space and then updates the centroid of the latent space incrementally by new incoming data. In the online learning, the algorithm continues learning by using the updated centroid. Through experiments using public underwater acoustic data, the proposed online anomaly detection algorithm takes only approximately 2 % additional learning time for the incremental centroid update and learning. Nevertheless, the proposed algorithm shows 19.10 % improvement in Area Under the receiver operating characteristic Curve (AUC) performance compared to the offline learning model when new incoming normal data comes.

• Journal of Korean Academy of Nursing
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• v.33 no.2
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• pp.162-169
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• 2003

Purpose: This study was to compare the predictive validity of Norton Scale(1962), Cubbin & Jackson Scale(1991), and Song & Choi Scale(1991). Method: Data were collected three times per week from 48~72hours after admission based on the four pressure sore risk assessment scales and a skin assessment tool for pressure sore on 112 intensive care unit(ICU) patients in a educational hospital Ulsan during Dec, 11, 2000 to Feb, 10, 2001. Four indices of validity and area under the curve(AUC) of receiver operating characteristic(ROC) were calculated. Result: Based on the cut off point presented by the developer, sensitivity, specificity, positive predictive value, negative predictive value were as follows : Norton Scale : 97%, 18%, 35%, 93% respectively; Cubbin & Jackson Scale : 89%, 61%, 51%, 92%, respectively; and Song & Choi Scale : 100%, 18%, 36%, 100% respectively. Area under the curves(AUC) of receiver operating characteristic(ROC) were Norton Scale .737, Cubbin & Jackson Scale .826, Song & Choi Scale .683. Conclusion: The Cubbin & Jackson Scale was found to be the most valid pressure sore risk assessment tool. Further studies on patients with chronic conditions may be helpful to validate this finding.