Polina Golland

The paper combines an organ chip platform with deep learning for drug response analysis in cancer models, showing improved accuracy over traditional methods.

This paper introduces a Bayesian segmentation algorithm for thalamic nuclei using diffusion MRI and an improved histological atlas, showing improved accuracy in identifying nuclei and detecting Alzheimer's disease involvement.

This paper develops a radiomic signature from T2-FLAIR MRI images to predict white matter hyperintensities burden and links it to clinical phenotypes.

The paper presents an automated pipeline for quantifying white matter hyperintensity in acute ischemic stroke cohorts, showing improved accuracy and enabling large-scale analysis.

This paper introduces effective reserve (eR), a latent variable derived from clinical and imaging data, to improve prediction of functional outcomes after acute ischemic stroke.