Author

D. Rueckert

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Open access Jul 2026

Addressing benchmarking gaps in large language models for health and medicine with dynamic red-teaming

A Dynamic, Automatic and Systematic red-teaming audit framework that continuously stress-tests LLMs for health across four safety-critical axes: robustness, privacy, bias and hallucination, which provides a scalable framework for surfacing latent risks before such systems are deployed in consumer-facing health assistants and broader clinical workflows.

Jiazhen Pan, Bailiang Jian, Paul Hager et al. · Nature Health · 0 citations

#machine learning Preprint Aug 2026

Primitive Representation Learning for Unsupervised Dynamic Contrast Enhanced MRI Reconstruction

This work proposes a multi-dimensional, primitive based framework for dynamic contrast-enhanced MRI reconstruction that disentangles the underlying anatomy, the dynamic contrast enhancement, and residual motion into separate temporal basis functions, thereby enabling a geometrical interpretation of the representation.

Veronika Spieker, Wenqi Huang, Cemre Ariyurek et al. · 0 citations