Results 41 to 50 of about 2,919,066 (271)
Semiparametric Estimation of the Covariate-Specific ROC Curve in Presence of Ignorable Verification Bias [PDF]
, 2011 Covariate-specific ROC curves are often used to evaluate the classification accuracy of a medical diagnostic test or a biomarker, when the accuracy of the test is associated with certain covariates. In many large-scale screening tests, the gold standard
Liu, Danping, Zhou, Xiao-Hua
core +2 more sources
Comparing ROC Curves Derived From Regression Models [PDF]
, 2011 In constructing predictive models, investigators frequently assess the incremental value of a predictive marker by comparing the ROC curve generated from the predictive model including the new marker with the ROC curve from the model excluding the new ...
Begg, Colin B +2 more
core +2 more sources
Prequential AUC: properties of the area under the ROC curve for data streams with concept drift
Knowledge and Information Systems, 2017 Modern data-driven systems often require classifiers capable of dealing with streaming imbalanced data and concept changes. The assessment of learning algorithms in such scenarios is still a challenge, as existing online evaluation measures focus on ...
D. Brzezinski, J. Stefanowski
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Neuropsychological complications may impair the qualitative prognosis of patients with pediatric brain tumors. However, multifaceted evaluations cannot be conducted in all patients because they are time consuming and burdensome for patients.
Ami Tabata +9 more
wiley +1 more source
Molecular Oncology, EarlyView.We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck +12 more
wiley +1 more source
Semi-Parametric Maximum Likelihood Estimates for ROC Curves of Continuous-Scale Tests [PDF]
, 2008 In this paper, we propose a new semi-parametric maximum likelihood (ML) estimate of an ROC curve that satisfies the property of invariance of the ROC curve and is easy to compute.
Lin, Huazhen, Zhou, Xiao-Hua
core +3 more sources
nsROC: An R package for Non-Standard ROC Curve Analysis
The R Journal, 2018 The receiver operating characteristic (ROC) curve is a graphical method which has become standard in the analysis of diagnostic markers, that is, in the study of the classification ability of a numerical variable.
Sonia Pérez-Fernández +3 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.We developed a cost‐effective methylation‐specific droplet digital PCR multiplex assay containing tissue‐conserved and tumor‐specific methylation markers. The assay can detect circulating tumor DNA with high accuracy in patients with localized and metastatic colorectal cancer.
Luisa Matos do Canto +8 more
wiley +1 more source
BMC Medical Informatics and Decision Making, 2011 Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated ...
Zumbrunn Thomas, Rousson Valentin
doaj +1 more source
Molecular Oncology, EarlyView.Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley +5 more
wiley +1 more source