Received operating characteristic ROC curve

The Role of Receiver Operating Characteristic (ROC) Curves in the Evaluation... 

A new tumor marker is evaluated using the same criteria used for many diagnostic tests (i.e., sensitivity, specificity, and accuracy). The diagnostic sensitivity and specificity are best represented by a receiver operating characteristic (ROC) curve. The ROC curve is constructed with the true-positive rate versus false-positive rate at various decision levels. As a test improves in its diagnostic performance, it shifts upward and to the left as the true-positive rate increases and the false-positive rate decreases. 

Fig. 11.8. A binormal receiver operating characteristic (ROC) curve (solid line) plotting the sensitivity versus 1-specificity using the 850 nm OCT attenuation coefficient to distinguish between eariy caries and heaithy enamel. The dashed line represents the ROC curve for a nondiscriminatory test. The markers on the curve represent setting an OCT attenuation coefficient threshold between caries and healthy enamel at 0.9 rnrri 1 (diamond) and at 1.08 rrirri 1 (star)...

Enrichment based methods. These focus on recovering active molecules from a test database in which a small number of known actives have been hidden in a large database of randomly selected compounds. Database mining and the utilization of receiver operating characteristic (ROC) curves [43] can be included in this category. 

This maximizes Se (Se l). However, specificity will be minimized as most of the inactive molecules will be in the selection. The situation is reversed in the case where n is very small (n 0). Consequently, one cannot optimize both Se and Sp at the same time and a trade-off is to be determined. If one can choose to rely on one of the above metrics to find an optimum, we have recently advocated the use of a simpler graphical technique which has been adopted as a gold standard in many other research areas the receiver operating characteristic (ROC) curve method [53]. 

Constructing a receiver operating characteristic (ROC) curve, which is a quantitative analysis, it showed that a rapamycin blood concentration of >8 ng/mL was the proper cutoff to define high blood concentration of the drug, and that it was in agreement with the mean rapamycin blood concentration in patients having no restenosis (7.9 ng/mL). 

The selectivity of the sensor is determined by the efficiency of the coating material. Developing selective coatings is an ongoing research area. Figure 3 shows a useful metric for sensor performance called the receiver operating characteristic (ROC) curve [16]. 

Metz, C. E Herman, B. A. Shen, J. H. (1998b). Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed data. Stat Med 17, 1033-53. 

The recognition accuracy estimation described above faces one very important problem what is the best choice for the threshold value 0 To solve this problem, statistical decision theory is used. ° The basis for this is an analysis of the so-called the Received Operating Characteristic (ROC) curve. By tradition, ROC is plotted as a function of true positive rate TPj TP + FN) (or sensitivity) versus false positive rate FPj TN+FP) (or 1-Specificity) for all possible threshold values 0. Figure 6.5 presents an example of such a ROC curve for the results obtained with our computer program PASS in predicting antineoplastic activity. 

When a new test is developed or an old test is applied to a new clinical question, users need information about the extent of agreement of the test s results with the correct diagnoses of patients. For this purpose, researchers design studies in which results from the new test are compared with the results obtained with the reference standard on the same patients. The results of the comparison can be expressed in a number of ways, including sensitivity and specificity, predictive values, likelihood ratios, diagnostic odds ratios, and areas under receiver operating characteristic (ROC) curves (see Chapter 15). We will refer to such studies as diagnostic accuracy studies. 

Figure 24-10 Receiver operating characteristic (ROC) curves comparing creatinine and cystatin C in the assessment of GFR. Non parametric ROC plots were constructed to assess the diagnostic accuracy of serum concentrations of cystatin C and creatinine in distinguishing between normal and reduced GFR (less than 80mL/min per 1.73 m ) in 51 patients with various renal conditions. (From Kyhse-Andersen j, Schmidt C, Nordin C, et af. Serum cystatin C, determined by a rapid, automated particle-enhanced turbidimetric method, is a better marker than serum creatinine for glomerular filtration rate. Clin Chem 1994 40 l92l-6.)...

The aim of BPS-MS approach presented here can be summarized by comparing the simulated receiver operator characteristic (ROC) curves shown in Figure 1. Each additional dimension of analysis (a distinct pulse shape, that yields distinct mass spectrum) enlarges the area under the curve and therefore the confidence of the measurement. 

Evaluation of the selectivity of each model by one of the discrimination measures, e.g., area under the receiver operating characteristic (ROC) curve (AUC) ... 

The data are often plotted as a Receiver Operating Characteristics (ROC) curve, which plots the TPP vs. the false positive rate or probability (FPP), where ... 

Fig. 6 Receiver operating characteristics (ROCs) curve for typical sensor behavior. The diagonal line represents a sensor with no selectivity and the two upper curves improved sensor performance in both sensitivity and specificity...

Jensen, A. L., M. T. Thofner, and L. Iverasen. 1996. Application of receiver operating characteristic (ROC) curves to veterinary clinical pathology. Comparative Hematology International 6 176-181. 

To compare the performance of a number of classification models, a receiver operating characteristic (ROC) curve can be used. These were first developed to correctly detect Japanese aircraft from their radar signatures after the attack on Pearl Harbour. ROC curves are widely used in evidence-based medicine. The y-axis is the sensitivity (true positive rate) and the x-axis is (1-specificity) the false... 

Fundamental clinical laboratory test performance can be described in terms of accuracy, or the ability to correctly classify subjects into clinically relevant subgroups. Receiver operating characteristic (ROC) curves demonstrate the limits of a given test to detect the alternative states of interest over the complete spectrum of operating conditions, providing a comprehensive and pure index of accuracy. 

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