Author

S. Ziegelmayer

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Open access Sep 2026

Correlation of CT-Derived Quantitative Image Features and Inflammatory Laboratory Markers with Length of Hospital Stay in Patients with Pyelonephritis

Background/Objectives: To assess associations between quantitative computed tomography (CT) features, inflammatory markers, and length of hospital stay (LOS) in acute pyelonephritis (APN). Methods: This retrospective single-center study included 82 patients with CT-confirmed APN. Two radiologists quantified renal perfu...

Markus M. Graf, T. Lemke, A. Marka et al. · Diagnostics · 0 citations

Review Open access Aug 2026

Artificial Intelligence-Assisted Chest Radiography: A Prospective Crossover Multi-Reader Study on Diagnostic Performance and Workflow Efficiency.

RATIONALE AND OBJECTIVES To evaluate the impact of four commercially available AI solutions for chest radiography on diagnostic performance, workflow efficiency, and clinical decision-making in a real-world setting. MATERIALS AND METHODS In this prospective, monocentric, crossover reader study, five readers (one to s...

T. Lemke, A. Marka, P. Prucker et al. · Academic Radiology · 0 citations

#computer vision Jul 2026

Self-supervision drives representational convergence in medical foundation models more than clinical supervision

Medical image encoders from different groups are increasingly treated as interchangeable, on the assumption that scale and clinical supervision concentrate their representations onto a shared structure. Whether this convergence is real, what produces it, and whether it is clinically usable are untested, and the similar...

Soroosh Tayebi Arasteh, S. Ziegelmayer, Mahshad Lotfinia et al. · arXiv.org · 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

Jul 2026

Information-seeking failures of large language models in agentic clinical reasoning

Large language models achieve high scores on medical knowledge assessments, yet clinical reasoning requires actively deciding what to investigate under uncertainty. We developed an agentic evaluation framework in hematologic oncology in which models must proactively request clinical data across three sequential rounds...

K. Braitsch, L. Schmalbrock, Theresa Weltermann et al. · arXiv.org · 1 citation