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Soroosh Tayebi Arasteh

Principal Investigator

RWTH Aachen University

Germany

Research Interests

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Articles (20)

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2026

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2023

Collaborators (9)

Nicholas West

University of Leeds School of Medicine

UNITED KINGDOM

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Sven Nebelung

University Hospital RWTH Aachen

GERMANY

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Keno K. Bressem

GERMANY

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Gustav Müller-Franzes

RWTH Aachen University

GERMANY

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Daniel Rueckert

Director, Alexander von Humboldt Professor for AI

Technical University of Munich

GERMANY

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Jakob Nikolas Kather

Professor of Clinical Artificial Intelligence

TU Dresden

GERMANY

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Christiane K. Kuhl

University Hospital RWTH Aachen

GERMANY

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Teresa Lemainque

RWTH Aachen University

GERMANY

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Behrus Hinrichs-Puladi

Specialist in Oral and Maxillofacial Surgery

University Hospital RWTH Aachen

GERMANY

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Soroosh Tayebi Arasteh

Research Interests

Explore related searches

Articles (20)

Retrieval-augmented reasoning reshapes collective reliability in text-based radiology question answering

SteuerLLM: local specialized large language model for German tax law analysis

When Framing Shapes the Answer: Cognitive Bias and Large Language Model Reliability in Radiology

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications

RadioRAG: Online Retrieval–Augmented Generation for Radiology Question Answering

Multi-step retrieval and reasoning improves radiology question answering with large language models

Differential privacy enables fair and accurate AI-based analysis of speech disorders while protecting patient data

From large language models to multimodal AI: a scoping review on the potential of generative AI in medicine

Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representations

Intraindividual Comparison of Different Methods for Automated BPE Assessment at Breast MRI: A Call for Standardization

Encrypted federated learning for secure decentralized collaboration in cancer image analysis

Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging

The Treasure Trove Hidden in Plain Sight: The Utility of GPT-4 in Chest Radiograph Evaluation

Large language models streamline automated machine learning for clinical studies

Securing Collaborative Medical AI by Using Differential Privacy: Domain Transfer for Classification of Chest Radiographs

Addressing challenges in speaker anonymization to maintain utility while ensuring privacy of pathological speech

Accelerating breast MRI acquisition with generative AI models

Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images.

Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning

Collaborators (9)

Nicholas West

Sven Nebelung

Keno K. Bressem

Gustav Müller-Franzes

Daniel Rueckert

Jakob Nikolas Kather

Christiane K. Kuhl

Teresa Lemainque

Behrus Hinrichs-Puladi

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