Receiver operator characteristic (ROC) analysis without truth.
about
Evaluation of diagnostic accuracy in detecting ordered symptom statuses without a gold standard.Interval estimation for the difference in paired areas under the ROC curves in the absence of a gold standard test.On the convexity of ROC curves estimated from radiological test resultsLatent class modeling approaches for assessing diagnostic error without a gold standard: with applications to p53 immunohistochemical assays in bladder tumors.Estimation in medical imaging without a gold standardObjective comparison of quantitative imaging modalities without the use of a gold standard.Objective evaluation of reconstruction methods for quantitative SPECT imaging in the absence of ground truth.Comparing cardiac ejection fraction estimation algorithms without a gold standardBayesian analysis and classification of two enzyme-linked immunosorbent assay tests without a gold standard.Estimating confidence intervals for the difference in diagnostic accuracy with three ordinal diagnostic categories without a gold standard.Task-based evaluation of segmentation algorithms for diffusion-weighted MRI without using a gold standard.Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images.A sequential classification rule based on multiple quantitative tests in the absence of a gold standard.Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.Flexible regression models for ROC and risk analysis, with or without a gold standard.Evaluating Estimation Techniques in Medical Imaging Without a Gold Standard: Experimental Validation.Strategies to configure image analysis algorithms for clinical usage.The efficacy of diagnostic imaging.Random effects models for assessing diagnostic accuracy of traditional Chinese doctors in absence of a gold standard.Modeling rater diagnostic skills in binary classification processes.Model-based clustering for assessing the prognostic value of imaging biomarkers and mixed type tests.Estimating diagnostic test accuracy using a "fuzzy gold standard".Probit Latent Class Analysis with Dichotomous or Ordered Category Measures: Conditional Independence/Dependence Models
P2860
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P2860
Receiver operator characteristic (ROC) analysis without truth.
description
1990 nî lūn-bûn
@nan
1990年の論文
@ja
1990年学术文章
@wuu
1990年学术文章
@zh
1990年学术文章
@zh-cn
1990年学术文章
@zh-hans
1990年学术文章
@zh-my
1990年学术文章
@zh-sg
1990年學術文章
@yue
1990年學術文章
@zh-hant
name
Receiver operator characteristic (ROC) analysis without truth.
@en
Receiver operator characteristic
@nl
type
label
Receiver operator characteristic (ROC) analysis without truth.
@en
Receiver operator characteristic
@nl
prefLabel
Receiver operator characteristic (ROC) analysis without truth.
@en
Receiver operator characteristic
@nl
P2093
P2860
P1476
Receiver operator characteristic (ROC) analysis without truth.
@en
P2093
M J Bronskill
R M Henkelman
P2860
P356
10.1177/0272989X9001000105
P577
1990-01-01T00:00:00Z