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Robust sensitivity control in digital pathology via tile score distribution matching

Predicting gene essentiality and drug response from perturbation screens in preclinical cancer models with LEAP: Layered Ensemble of Autoencoders and Predictors

Distilling foundation models for robust and efficient models in digital pathology

FedPyDESeq2: a federated framework for bulk RNA-seq differential expression analysis

Transcriptome Analysis of Archived Tumor Tissues by Visium, GeoMx DSP, and Chromium Methods Reveals Inter- and Intra-Patient Heterogeneity

Legitimate ground-truth-free metrics for deep uncertainty classification scoring

Phikon-v2, A large and public feature extractor for biomarker prediction

A deep learning-based multiscale integration of spatial omics with tumor morphology.

Robust Evaluation of Deep Learning-based Representation Methods for Survival and Gene Essentiality Prediction on Bulk RNA-seq Data

Subgroup analysis methods for time-to-event outcomes in heterogeneous randomized controlled trials

Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery

FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings