• Journal of the Korean Data and Information Science Society
• /
• v.24 no.6
• /
• pp.1489-1496
• /
• 2013

Consider the ROC surface which is a generalization of the ROC curve for three-class diagnostic problems. In this work, we propose ve criteria for the three-class ROC surface by extending the Youden index, the sum of sensitivity and specificity, the maximum vertical distance, the amended closest-to-(0,1) and the true rate. It may be concluded that these five criteria can be expressed as a function of two Kolmogorov-Smirnov statistics. A paired optimal thresholds could be obtained simultaneously from the ROC surface. It is found that the paired optimal thresholds selected from the ROC surface are equivalent to the two optimal thresholds found from the two ROC curves.

• The Korean Journal of Applied Statistics
• /
• v.26 no.6
• /
• pp.977-985
• /
• 2013

Many situations are classified into more than two categories in real world. In this work, we consider ROC surface and VUS, which are graphical representation methods for classification models with three categories. The standard criteria of AUC for the probability of default based on Basel II is extended to the VUS for ROC surface; therefore, the standardized criteria of VUS for the classification model is proposed. The ranges of AUC, K-S and mean difference statistics corresponding to VUS values for each class of the standard criteria are obtained. The standard criteria of VUS for ROC surface can be established by exploring the relationships of these statistics.

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

• Proceedings of the CALSEC Conference
• /
• 2001.02a
• /
• pp.83-96
• /
• 2001

정의 : 무기체계의 설계/개발 특성을 식별, 문서화(규격서, 도면 등)하고, 기술발전에 따라 성능개량을 추진하는 제반 기술정보를 기록 및 유지하는 활동 ㆍ 최적의 순기비용으로 장비요구 성능충족(ROC 만족) ㆍ 계약업무 일관성 도모 및 경쟁입찰에 의한 획득 ㆍ 표준화 및 통일성(중략)

• Proceedings of the CALSEC Conference
• /
• 1999.11a
• /
• pp.417-431
• /
• 1999

정의: 무기체계의 설계/개발 특성을 식별, 문서화(규격서,도면 등)하고, 기술발전에 따라 성능개량을 추진하는 제반 기술정보를 기록 및 유지하는 활동 목적: ㆍ최적의 순기비용으로 장비요구 성능충족(ROC 만족) ㆍ계약업무 일관성 도모 및 경쟁입찰에 의한 획득 ㆍ표준화 및 통일성 (중략)

• Journal of Biomedical Engineering Research
• /
• v.31 no.3
• /
• pp.177-186
• /
• 2010

In 3D ultrasound color Doppler imaging (CDI), 8-16 pulse transmissions (ensembles) per each scanline are used for effective clutter rejection and flow estimation, but it yields a low volume acquisition rate. In this paper, we have evaluated three flow estimation methods: autoregression (AR), eigendecomposition (ED), and autocorrelation combined with adaptive clutter rejection (AC-ACR) for a small ensemble size (E=4). The performance of AR, ED and AC-ACR methods was compared using 2D and 3D in vivo data acquired under different clutter conditions (common carotid artery, kidney and liver). To evaluate the effectiveness of three methods, receiver operating characteristic (ROC) curves were generated. For 2D kidney in vivo data, the AC-ACR method outperforms the AR and ED methods in terms of the area under the ROC curve (AUC) (0.852 vs. 0.793 and 0.813, respectively). Similarly, the AC-ACR method shows higher AUC values for 2D liver in vivo data compared to the AR and ED methods (0.855 vs. 0.807 and 0.823, respectively). For the common carotid artery data, the AR provides higher AUC values, but it suffers from biased estimates. For 3D in vivo data acquired from a kidney transplant patient, the AC-ACR with E=4 provides an AUC value of 0.799. These in vivo experiment results indicate that the AC-ACR method can provide more robust flow estimates compared to the AR and ED methods with a small ensemble size.

• Journal of Microbiology and Biotechnology
• /
• v.31 no.3
• /
• pp.447-455
• /
• 2021

Strains of four Bacillus spp. were respectively inoculated into sterilized soybeans and the free amino acid profiles of the resulting cultures were analyzed to discern their metabolic traits. After 30 days of culture, B. licheniformis showed the highest production of serine, threonine, and glutamic acid; B. subtilis exhibited the highest production of alanine, asparagine, glycine, leucine, proline, tryptophan, and lysine. B. velezensis increased the γ-aminobutyric acid (GABA) concentration to >200% of that in the control samples. B. sonorensis produced a somewhat similar amino acid profile with B. licheniformis. Comparative genomic analysis of the four Bacillus strains and the genetic profiles of the produced free amino acids revealed that genes involved in glutamate and arginine metabolism were not common to the four strains. The genes gadA/B (encoding a glutamate decarboxylase), rocE (amino acid permease), and puuD (γ-glutamyl-γ-aminobutyrate hydrolase) determined GABA production, and their presence was species-specific. Taken together, B. licheniformis and B. velezensis were respectively shown to have high potential to increase concentrations of glutamic acid and GABA, while B. subtilis has the ability to increase essential amino acid concentrations in fermented soybean foods.

• International Journal of Computer Science & Network Security
• /
• v.24 no.4
• /
• pp.1-10
• /
• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• Korean Journal of Biological Psychiatry
• /
• v.27 no.2
• /
• pp.94-100
• /
• 2020

Objectives Amyloid β positron emission tomography (Aβ PET) is widely used as a diagnostic tool in patients who have symptoms of cognitive impairment, however, this diagnostic examination is too expensive. Thus, predicting the positivity of Aβ PET before patients undergo the examination is essential. We aimed to analyze clinical predictors of patients who underwent Aβ PET retrospectively, and to develop a predicting model of Aβ PET positivity. Methods 468 patients who underwent Aβ PET with cognitive impairment were recruited and their clinical indicators were analyzed retrospectively. We specified the primary outcome as Aβ PET positivity, and included variables such as age, sex, body mass index, diastolic blood pressure, systolic blood pressure, education, dementia family history, Mini Mental Status Examination (MMSE), Clinical Dementia Rating (CDR), Clinical Dementia Rating-Sum of Box (CDR-SB), hypertension (HTN), diabetes mellitus (DM) and presence of apolipoprotein E (ApoE) E4 as potential predictors. We developed three final models of amyloid positivity prediction for total subjects, mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia using a multivariate stepwise logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was performed and the area under curve (AUC) value was calculated for the ROC curve. Results Aβ PET negative patients were 49.6% (n = 232), and Aβ PET positive patients were 50.4% (n = 236). In the final model of all subjects, older age, female sex, presence of ApoE E4 and lower MMSE are associated with Aβ PET positivity. The AUC value was 0.296. In the final model of MCI subjects (n = 244), older age and presence of ApoE E4 are associated with Aβ PET positivity. The AUC value was 0.725. In the final model of AD subjects (n = 173), lower MMSE scores, the presence of ApoE E4 and history of HTN are associated with Aβ PET positivity. The AUC value was 0.681. Conclusions The cerebral amyloid positivity model, which was based on commonly available clinical indicators, can be useful for prediction of amyloid PET positivity in MCI or AD patients.

• Atmosphere
• /
• v.23 no.1
• /
• pp.113-121
• /
• 2013

The objective of this study is to develop and evaluate the system to produce the real-time ensemble drought prediction data. Ensemble drought prediction consists of 3 processes (meteorological outlook using the multi-initial conditions, hydrological analysis and drought index calculation) therefore, more processing time and data is required than that of single member. For ensemble drought prediction, data process time is optimized and hardware of existing system is upgraded. Ensemble drought data is estimated for year 2012 and to evaluate the accuracy of drought prediction data by using ROC (Relative Operating Characteristics) analysis. We obtained 5 ensembles as optimal number and predicted drought condition for every tenth day i.e. 5th, 15th and 25th of each month. The drought indices used are SPI (Standard Precipitation Index), SRI (Standard Runoff Index), SSI (Standard Soil moisture Index). Drought conditions were determined based on results obtained for each ensemble member. Overall the results showed higher accuracy using ensemble members as compared to single. The ROC score of SRI and SSI showed significant improvement in drought period however SPI was higher in the demise period. The proposed ensemble drought prediction system can be contributed to drought forecasting techniques in Korea.