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Author

I. Pretzell

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Open access Jul 2026

LLM-Generated Lay-Language Protocols for Molecular Tumor Board Patients: Evaluation of Quality and Clinical Usability

The low paragraph-level error rate and favorable PPEE suggest that structured open-weight LLM generation may be a useful drafting support in a clinician-supervised setting, and a proposed evaluation framework for patient-facing text generation is developed.

T. Pakull, Noëlle Bender, Sven Benson et al. · 0 citations
Open access Jul 2026

An explainable transformer model learning from entire treatment timelines for pan-cancer risk profiling across healthcare systems

Chronicle is introduced, an explainable transformer that learns from entire patient trajectories, predicts diverse clinical outcomes throughout the disease course while capturing both short- and long-term temporal dependencies, providing a scalable framework to support individualized treatment decisions.

P. Keyl, N. Kiermeyer, J. Bosserhoff et al. · 0 citations

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