4 citations · 10 across the 11 of their papers we have counts for
11 papers
Tumor Radiogenomics with Bayesian Layered Variable Selection
Shariq Mohammed, Sebastian Kurtek, Karthik Bharath +2
We propose a statistical framework to integrate radiological magnetic resonance imaging (MRI) and genomic data to identify the underlying radiogenomic associations in lower grade g…
RADIOHEAD: Radiogenomic Analysis Incorporating Tumor Heterogeneity in Imaging Through Densities
Shariq Mohammed, Karthik Bharath, Sebastian Kurtek +2
Recent technological advancements have enabled detailed investigation of associations between the molecular architecture and tumor heterogeneity, through multi-source integration o…
Integrative Bayesian models using Post-selective Inference: a case study in Radiogenomics
Snigdha Panigrahi, Shariq Mohammed, Arvind Rao +1
Integrative analyses based on statistically relevant associations between genomics and a wealth of intermediary phenotypes (such as imaging) provide vital insights into their clini…
Regression Analyses of Distributions using Quantile Functional Regression
Hojin Yang, Veerabhadran Baladandayuthapani, Arvind U. K. Rao +1
Radiomics involves the study of tumor images to identify quantitative markers explaining cancer heterogeneity. The predominant approach is to extract hundreds to thousands of image…
Radiologic Image-based Statistical Shape Analysis of Brain Tumors
Karthik Bharath, Sebastian Kurtek, Arvind Rao +1
We propose a curve-based Riemannian-geometric approach for general shape-based statistical analyses of tumors obtained from radiologic images. A key component of the framework is a…
Going off the Grid: Iterative Model Selection for Biclustered Matrix Completion
Eric Chi, Liuiyi Hu, Arvind K. Saibaba +1
We consider the problem of performing matrix completion with side information on row-by-row and column-by-column similarities. We build upon recent proposals for matrix estimation…