All Outputs (3)

Tumor radiogenomics in gliomas with Bayesian layered variable selection (2023)
Journal Article
Mohammed, S., Kurtek, S., Bharath, K., Rao, A., & Baladandayuthapani, V. (2023). Tumor radiogenomics in gliomas with Bayesian layered variable selection. Medical Image Analysis, 90, Article 102964. https://doi.org/10.1016/j.media.2023.102964

We propose a statistical framework to analyze radiological magnetic resonance imaging (MRI) and genomic data to identify the underlying radiogenomic associations in lower grade gliomas (LGG). We devise a novel imaging phenotype by dividing the tumor... Read More about Tumor radiogenomics in gliomas with Bayesian layered variable selection.

Probabilistic Learning of Treatment Trees in Cancer (2023)
Journal Article
Yao, T., Wu, Z., Bharath, K., Li, J., & Baladandayuthapani, V. (2023). Probabilistic Learning of Treatment Trees in Cancer. Annals of Applied Statistics, 17(3), 1884-1908. https://doi.org/10.1214/22-AOAS1696

Accurate identification of synergistic treatment combinations and their underlying biological mechanisms is critical across many disease domains, especially cancer. In translational oncology research, preclinical systems, such as patient-derived xeno... Read More about Probabilistic Learning of Treatment Trees in Cancer.

Spatially penalized registration of multivariate functional data (2023)
Journal Article
Guo, X., Kurtek, S., & Bharath, K. (2023). Spatially penalized registration of multivariate functional data. Spatial Statistics, 56, Article 100760. https://doi.org/10.1016/j.spasta.2023.100760

Registration of multivariate functional data involves handling of both cross-component and cross-observation phase variations. Allowing for the two phase variations to be modelled as general diffeomorphic time warpings, in this work we focus on the h... Read More about Spatially penalized registration of multivariate functional data.