Predictive classification of correlated targets with application to detection of metastatic cancer using functional CT imaging
DOI10.1111/biom.12304zbMath1419.62472OpenAlexW1497170325WikidataQ36073298 ScholiaQ36073298MaRDI QIDQ2803502
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Publication date: 4 May 2016
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc4575264
spatial correlationBayesian decision analysiscancer detectionmetastatic liver cancerperfusion imaging
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)
Cites Work
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- Spatio-temporal stationary covariance models
- Anisotropic Matérn correlation and spatial prediction using REML
- A likelihood ratio test for separability of covariances
- Discriminant Analysis for Longitudinal Data with Multiple Continuous Responses and Possibly Missing Data
- A Predictive Approach to Model Selection
- Bayesian Measures of Model Complexity and Fit
- Robust Classification of Functional and Quantitative Image Data Using Functional Mixed Models
- Semiparametric Bayesian Classification with longitudinal Markers
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