Nonparametric estimation of conditional ROC curves: application to discrimination tasks in computerized detection of early breast cancer

DOI10.1016/J.CSDA.2007.09.013zbMath1452.62826OpenAlexW2054320779WikidataQ61849295 ScholiaQ61849295MaRDI QIDQ1023591

Carmen Cadarso-Suárez, Ignacio López-de-Ullibarri, Ricardo Cao, María José Lado

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.09.013

zbMATH Keywords

bootstrapsmoothinglocal linear estimatorbandwidth selectionconditional distributionROC curvemicrocalcificationscomputer-aided diagnosis

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric tolerance and confidence regions (62G15) Nonparametric statistical resampling methods (62G09)

Related Items (11)

Three-group ROC analysis: a nonparametric predictive approach ⋮ A non-parametric test for comparing conditional ROC curves ⋮ ROC Curves in Non-Parametric Location-Scale Regression Models ⋮ Estimation of the volume under a ROC surface in presence of covariates ⋮ Modelling receiver operating characteristic curves using Gaussian mixtures ⋮ A new flexible direct ROC regression model: application to the detection of cardiovascular risk factors by anthropometric measures ⋮ Comparative study of ROC regression techniques -- applications for the computer-aided diagnostic system in breast cancer detection ⋮ Powerful nonparametric statistics to compare k independent ROC curves ⋮ Editorial: Computational statistics within clinical research ⋮ ROC curve and covariates: extending induced methodology to the non-parametric framework ⋮ Unnamed Item

Uses Software

• gamair
• bootstrap

Cites Work

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• Local linear smoothing of receiver operating characteristic (ROC) curves
• Improved methods for bandwidth selection when estimating ROC curves.
• ROC curve estimation based on local smoothing
• Nonparametric confidence intervals for receiver operating characteristic curves
• Empirical likelihood confidence regions for comparison distributions and ROC curves
• Three Approaches to Regression Analysis of Receiver Operating Characteristic Curves for Continuous Test Results

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