Journal Club

He et al. - Deep Residual Learning for Image Recognition

Oquab et al. - DINOv2 Learning Robust Visual Features without Supervision

Predicting Cancer Drug Response: The Advancements of DeepCDR's Hybrid Approach)

Ferraro et al. - MOViDA multiomics visible drug activity prediction with a biologically informed neural network model

Dosovitskiy et al. - An Image is Worth 16x16 Words Transformers for Image Recognition at Scale

Evaluating Partially Unknown Cancer Mutation Orders Using Mutual Hazard Networks

Beating the International Prognostic Index (IPI) for high-risk DLBCL patients

lirec: R package for _literatur research

Marker-guided cellular segmentation for integrative spatial analysis of immune cell populations in highly multiplexed immunofluorescent images

Context matters: Stratification effects on pancancer progression modelling

Update on UR IT-services and FDLP: Pathology Server Infrastructure & overview WSI conversion

Software for grup and variant comparison of exome sequencing data

Explainable AI for Bioinformatics: Methods, Tools and Applications - Introduction

Explainable AI for Bioinformatics: Methods, Tools and Applications - Techniques and methods for interpretable machine learning (Perturbing black-box models)

Explainable AI for Bioinformatics: Methods, Tools and Applications - Techniques and methods for interpretable ML: "Model surrogation strategies" and "Casual inference and contrastive explanations" as well as "Human-in-the-loop and knowledge-based approaches" and "Measure of interpretability and explainability"

Explainable AI for Bioinformatics: Methods, Tools and Applications - Interpretable machine learning tools and libraries

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

Beating the International Prognostic Index (IPI) for high-risk DLBCL patients

Detecting anomalies in cancer cell line drug response data

LASSO Ensembles

cell type-specific survival analysis using tissueResolver