Bayesian finite mixture of regression analysis for cancer based on histopathological imaging-environment interactions.

ABSTRACT: Cancer is a heterogeneous disease. Finite mixture of regression (FMR)-as an important heterogeneity analysis technique when an outcome variable is present-has been extensively employed in cancer research, revealing important differences in the associations between a cancer outcome/phenotype and covariates. Cancer FMR analysis has been based on clinical, demographic, and omics variables. A relatively recent and alternative source of data comes from histopathological images. Histopathological images have been long used for cancer diagnosis and staging. Recently, it has been shown that high-dimensional histopathological image features, which are extracted using automated digital image processing pipelines, are effective for modeling cancer outcomes/phenotypes. Histopathological imaging-enviro

SUBMITTER: Im Y 

PROVIDER: S-EPMC10102889 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature