Results 31 to 40 of about 2,515,870 (362)
Reasonably conduct the multiple Logistic regression analysis combined with the ROC curve analysis
Sichuan jingshen weisheng, 2022 The purpose of this paper was to introduce how to reasonably carry out the method of the multiple Logistic regression analysis by combining the ROC curve analysis. Firstly， it introduced two groups of the basic concepts related to the ROC curve analysis，
Hu Chunyan, Hu Liangping
doaj +1 more source
Diagnosis: shifting the ROC curve [PDF]
British Journal of General Practice, 2012 In 1972 Howie asked whether diagnosis was the Achilles heel of general practice.1 Accurate diagnosis was then, and remains, the fundamental concept of all medical practice. Are we any good at it now? This issue of the BJGP contains several papers on diagnosis and decision-making which shed light on this important area of practice. The results reported
openaire +3 more sources
ROC curves in cost space [PDF]
Machine Learning, 2013 ROC curves and cost curves are two popular ways of visualising classifier performance, finding appropriate thresholds according to the operating condition, and deriving useful aggregated measures such as the area under the ROC curve (AUC) or the area under the optimal cost curve.
Hernández Orallo, José +2 more
openaire +4 more sources
Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve [PDF]
Neural Computation, 2016 The area under the ROC curve (AUC) is a widely used performance measure in machine learning. Increasingly, however, in several applications, ranging from ranking to biometric screening to medicine, performance is measured not in terms of the full area ...
H. Narasimhan, S. Agarwal
semanticscholar +1 more source
Receiver Operating Characteristic Curve of Total Serum IgE in Allergic Patients [PDF]
مجلة الموصل للتمريض, 2017 Background and objective: Validity of continuous variable test like total serum IgE is performed by constructing Receiver Operating Characteristic (ROC) curve.
Haitham Bader Fathi
doaj +1 more source
easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment
The R Journal, 2016 ROC curve analysis is a fundamental tool for evaluating the performance of a marker in a number of research areas, e.g., biomedicine, bioinformatics, engineering etc., and is frequently used for discriminating cases from controls.
Dincer Goksuluk +3 more
semanticscholar +1 more source
The genetic interpretation of area under the ROC curve in genomic profiling. [PDF]
PLoS Genetics, 2010 Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease.
Naomi R Wray +3 more
doaj +1 more source
ADC cut points for chronic kidney disease in pathologically-proven cholangiocarcinoma
European Journal of Radiology Open, 2021 Purpose: Apparent diffusion coefficient (ADC) has been shown to indicate renal function in various conditions. As cholangiocarcinoma may have renal involvement due to immune complex-mediated glomerulonephritis, this study aimed to determine whether or ...
Jaturat Kanpittaya +3 more
doaj +1 more source
Disease Markers, 2018 The detection of serum biomarkers can aid in the diagnosis of lung cancer. In recent years, an increasing number of lung cancer markers have been identified, and these markers have been reported to have varying diagnostic values.
Qixian Yang +4 more
semanticscholar +1 more source
Nonparametric confidence intervals for the area under the ROC curve
Statistica, 2013 Following an idea by Jing et al. (2005), this paper combines the empirical likelihood for the mean functional with jackknife pseudo-values obtained from the Mann-Witney two-sample statistic.
Gianfranco Adimari
doaj +1 more source