5 papers
Learned Hemodynamic Coupling Inference in Resting-State Functional MRI
William Consagra, Eardi Lila
Functional magnetic resonance imaging (fMRI) provides an indirect measurement of neuronal activity via hemodynamic responses that vary across brain regions and individuals. Ignorin…
Asymmetric canonical correlation analysis of Riemannian and high-dimensional data
James Buenfil, Eardi Lila
In this paper, we introduce a novel statistical model for the integrative analysis of Riemannian-valued functional data and high-dimensional data. We apply this model to explore th…
Dimension-reduced outcome-weighted learning for estimating individualized treatment regimes in observational studies
Sungtaek Son, Eardi Lila, Kwun Chuen Gary Chan
Individualized treatment regimes (ITRs) aim to improve clinical outcomes by assigning treatment based on patient-specific characteristics. However, existing methods often struggle…
Why Text Prevails: Vision May Undermine Multimodal Medical Decision Making
Siyuan Dai, Lunxiao Li, Kun Zhao +6
With the rapid progress of large language models (LLMs), advanced multimodal large language models (MLLMs) have demonstrated impressive zero-shot capabilities on vision-language ta…
Genetic Regression Analysis of Human Brain Connectivity Using an Efficient Estimator of Genetic Covariance
Keshav Motwani, Ali Shojaie, Ariel Rokem +1
Non-invasive measurements of the human brain using magnetic resonance imaging (MRI) have significantly improved our understanding the brain's network organization by enabling measu…