Author

D. Rueckert

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#artificial intelligence Preprint Sep 2026

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Noah is a time-aware, task-agnostic, generative transformer model representing and forecasting the full multimodal patient journey, and is the first truly holistic generative model in its field, enabling autoregressive forecasting with optional time control, zero-shot classification, and counterfactual intervention sim...

Tobias Susetzky, R. Rehms, Dmitrii Seletkov et al. · 0 citations

Preprint Jul 2026

RadPRISM: Schema-stratified radiology-report supervision for concept-disentangled image representations and visual grounding

RadPRISM makes a clinician-defined radiology schema a designated stratification axis: an on-premise large language model extracts per-concept text spans from free-text reports, and each clinical concept is aligned in its own dedicated visual subspace, turning concept stratification into direct, top-level alignment supe...

Fabian Drexel, Marlene Fritzsche, Era Stambollxhiu et al. · 0 citations

#artificial intelligence Review Jun 2026

Are LLMs Ready to Assist Physicians? PhysAssistBench for Interactive Doctor-Patient-EHR Assistance

PhysAssistBench is introduced, a benchmark for interactive doctor-patient-EHR assistance that uses a scalable pipeline to construct agentic patients: interactive, record-grounded agents that turn static EHR records into multi-turn clinical scenarios while preserving clinical factuality.

T. Du, Peijie Yu, Sihan Shang et al. · arXiv.org · 0 citations