Addressing patient heterogeneity in disease predictive model development-Reference-Cited by-同舟云学术

Addressing patient heterogeneity in disease predictive model development

Published:2021-08 Issue: Volume: Page:
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Gao Xu¹^ORCID,Shen Weining¹^ORCID,Ning Jing²^ORCID,Feng Ziding³,Hu Jianhua⁴^ORCID

Affiliation:

1. Department of Statistics University of California Irvine California USA

2. Department of Biostatistics The University of Texas MD Anderson Cancer Center Houston Texas USA

3. Cancer Prevention Program Fred Hutchinson Cancer Research Center Seattle Washington USA

4. Department of Biostatistics Columbia University New York New York USA

Funder

National Science Foundation

National Institute of Allergy and Infectious Diseases

Simons Foundation

National Cancer Institute

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13514

Reference23 articles.

1. A Bayesian Approach to Subgroup Identification

2. Patterns of treatment effects in subsets of patients in clinical trials

3. Analysis of randomized comparative clinical trial data for personalized treatment selections

4. Hypothesis test for normal mixture models: The EM approach

5. Inference on the Order of a Normal Mixture

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