17 citations · 23 across the 3 of their papers we have counts for
3 papers
Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study
Sophia J. Wagner, Daniel Reisenbüchler, Nicholas P. West +28
Background: Deep learning (DL) can extract predictive and prognostic biomarkers from routine pathology slides in colorectal cancer. For example, a DL test for the diagnosis of micr…
Extending Models Via Gradient Boosting: An Application to Mendelian Models
Theodore Huang, Gregory Idos, Christine Hong +3
Improving existing widely-adopted prediction models is often a more efficient and robust way towards progress than training new models from scratch. Existing models may (a) incorpo…
Bayesian semiparametric analysis for two-phase studies of gene-environment interaction
Jaeil Ahn, Bhramar Mukherjee, Stephen B. Gruber +1
The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected subsample. It is natural to apply such a strategy for…