Author

B. Bozorgtabar

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Open access 2026

MBCE: Multi-Band Contrastive Encoding for Frequency-Aware Ultrasound Representation Learning

Ultrasound imaging relies on high-frequency sound waves to visualize internal anatomy in a non-invasive manner, yet automated analysis remains difficult due to low signal-to-noise ratios, speckle artifacts, and inconsistencies across scanners. These challenges are compounded by the scarcity of annotated datasets, limit...

Satyam Dubey, Tanushree Meena, B. Bozorgtabar et al. · IEEE Access · 0 citations

Preprint Sep 2026

Hierarchical Prompt Learning for Hyperbolic Vision-Language Models

Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstream tasks has largely relied on fixed prompts. Existing prompt learning methods, meanwhile, treat class labels as a flat set and do not exploit available taxonomic struc...

Andro Erdelez, Pascal Mettes, B. Bozorgtabar · 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