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stat.AP2020★ 1 cited
A Bayesian Nonparametric model for textural pattern heterogeneity
Xiao Li, Michele Guindani, Chaan S. Ng +1
Cancer radiomics is an emerging discipline promising to elucidate lesion phenotypes and tumor heterogeneity through patterns of enhancement, texture, morphology, and shape. The pre…
stat.ME2020★ 1 cited
A Common Atom Model for the Bayesian Nonparametric Analysis of Nested Data
Francesco Denti, Federico Camerlenghi, Michele Guindani +1
The use of high-dimensional data for targeted therapeutic interventions requires new ways to characterize the heterogeneity observed across subgroups of a specific population. In p…