3 papers
cs.LG2026
MoLF: Mixture-of-Latent-Flow for Pan-Cancer Spatial Gene Expression Prediction from Histology
Susu Hu, Stefanie Speidel
Inferring spatial transcriptomics (ST) from histology enables scalable histogenomic profiling, yet current methods are largely restricted to single-tissue models. This fragmentatio…
cs.LG2026
HistoPrism: Unlocking Functional Pathway Analysis from Pan-Cancer Histology via Gene Expression Prediction
Susu Hu, Qinghe Zeng, Nithya Bhasker +2
Predicting spatial gene expression from H&E histology offers a scalable and clinically accessible alternative to sequencing, but realizing clinical impact requires models that gene…
cs.LG2026
Adaptive-CaRe: Adaptive Causal Regularization for Robust Outcome Prediction
Nithya Bhasker, Fiona R. Kolbinger, Susu Hu +2
Accurate prediction of outcomes is crucial for clinical decision-making and personalized patient care. Supervised machine learning algorithms, which are commonly used for outcome p…