Joel Eliason

The paper introduces MAPLE, a framework that uses structured schemas to improve LLM-assisted QSP model calibration by ensuring data provenance and reducing hallucination.

SHADE models directional spatial associations in tissue microenvironments using a Bayesian framework, revealing biologically meaningful differences in immune and stromal organization in colorectal cancer.

This paper applies a multitype Gibbs point process model to colorectal cancer imaging data to analyze spatial interactions between cell types in the tumor microenvironment.

The paper introduces DIMPLE, an R package to quantify, visualize, and model cell-cell interactions from multiplex imaging data, and demonstrates its application to uncover associations between interactions and patient covariates.