Stephanie A. Harmon

OncoBERT models somatic mutations in cancer to identify patient-specific subtypes and improve prediction of treatment response by integrating mutational context with clinical biomarkers.

This paper introduces EXPAND, an interpretable AI model that predicts breast cancer subtypes and survival using nuclear features, achieving performance comparable to black-box models.

HistoTME-v2 predicts cell type-specific transcriptomic signatures and spatial distributions from H&E images, outperforming baselines across 25 tumor types and multiple validation datasets.

This study identifies conserved TME subtypes in canine and human osteosarcomas that predict clinical outcomes independently of known biomarkers.