Statistical Analysis of Quantitative Cancer Imaging Data
Recent advances in types and extant of medical imaging technologies has led to
proliferation of multimodal quantitative imaging data in cancer. Quantitative medical imaging …
proliferation of multimodal quantitative imaging data in cancer. Quantitative medical imaging …
[HTML][HTML] Tumor radiogenomics in gliomas with Bayesian layered variable selection
We propose a statistical framework to analyze radiological magnetic resonance imaging
(MRI) and genomic data to identify the underlying radiogenomic associations in lower grade …
(MRI) and genomic data to identify the underlying radiogenomic associations in lower grade …
GaWRDenMap: a quantitative framework to study the local variation in cell–cell interactions in pancreatic disease subtypes
Spatial pattern modelling concepts are being increasingly used in capturing disease
heterogeneity. Quantification of heterogeneity in the tumor microenvironment is extremely …
heterogeneity. Quantification of heterogeneity in the tumor microenvironment is extremely …
A Bayesian group selection with compositional responses for analysis of radiologic tumor proportions and their genomic determinants
The Supplementary Material contains details about group selection prior in univariable
regression models, sensitivity analysis, additional data analyses, MCMC diagnostics, and …
regression models, sensitivity analysis, additional data analyses, MCMC diagnostics, and …
Geometric framework for statistical analysis of eye tracking heat maps, with application to a tobacco waterpipe study
Health warning labels have been found to increase awareness of the harmful effects of
tobacco products. An eye tracking study was conducted to determine the optimal placement …
tobacco products. An eye tracking study was conducted to determine the optimal placement …
Distribution-on-scalar Single-index Quantile Regression Model for Handling Tumor Heterogeneity
This paper develops a distribution-on-scalar single-index quantile regression modeling
framework to investigate the relationship between cancer imaging responses and scalar …
framework to investigate the relationship between cancer imaging responses and scalar …
Assessment of Glioblastoma Multiforme Tumor Heterogeneity via MRI-Derived Shape and Intensity Features
We use a geometric approach to jointly characterize tumor shape and intensity along the
tumor contour, as captured in magnetic resonance images, in the context of glioblastoma …
tumor contour, as captured in magnetic resonance images, in the context of glioblastoma …
Bayesian Variable Selection in Double Generalized Linear Tweedie Spatial Process Models
Double generalized linear models provide a flexible framework for modeling data by
allowing the mean and the dispersion to vary across observations. Common members of the …
allowing the mean and the dispersion to vary across observations. Common members of the …
[PDF][PDF] Santhoshi Navaneetha Krishnan
A Patel - 2023 - repository.rice.edu
Cancer is the 2nd most common leading cause of death in the United States as of 2021, with
10 million deaths reported worldwide [4, 5]. Cancer is not a singular disease in itself; …
10 million deaths reported worldwide [4, 5]. Cancer is not a singular disease in itself; …
Functional Regression Models for Multi-Site Imaging Data Integration
H Dogra - 2024 - repository.lib.fsu.edu
In large-scale imaging studies, addressing heterogeneity presents a big challenge arising
from diverse geographic locations, variations in instrumentation, differences in image …
from diverse geographic locations, variations in instrumentation, differences in image …