A Bayesian nonparametric model for textural pattern heterogeneity-Reference-Cited by-同舟云学术

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A Bayesian nonparametric model for textural pattern heterogeneity

Published:2021-02-12 Issue:2 Volume:70 Page:459-480
ISSN:0035-9254
Container-title:Journal of the Royal Statistical Society: Series C (Applied Statistics)
language:en
Short-container-title:J R Stat Soc Series C

Author:

Li Xiao¹,Guindani Michele²,Ng Chaan S.³,Hobbs Brian P.⁴

Affiliation:

1. Personalized Healthcare Genentech, Inc. South San Francisco CA USA

2. Department of Statistics University of California Irvine CA USA

3. Department of Diagnostic Radiology The University of Texas MD Anderson Cancer Center Houston TX USA

4. Dell Medical School The University of Texas at Austin Austin TX USA

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssc.12469

Reference59 articles.

1. Erratum: Corrigendum: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

2. Diagnostic performance of 18-F-FDG-PET–CT in adrenal lesions using histopathology as reference standard

3. Statistical applications of the multivariate skew normal distribution

4. Non-parametric spatial models for clustered ordered periodontal data

5. Hierarchical Modeling and Analysis for Spatial Data

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2. Radiomics in Cross-Sectional Adrenal Imaging: A Systematic Review and Quality Assessment Study;Diagnostics;2022-02-24

3. Diagnostic Accuracy of CT Texture Analysis in Adrenal Masses: A Systematic Review;International Journal of Molecular Sciences;2022-01-07

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