Repurposing adult AI radiograph models for neonatal care through continual learning: an international multicentre study

Vishwanatha M. Rao*, Emma Chen*, Agustina Saenz*, Oishi Banerjee, Henrik Marklund, Lucas Bijnens, Sung Eun Kim, Evan Zucker, Susan Shelmerdine, Jeremy Palacio, Kent Ryan Kleinschmidt, Sathvik Suryadevara, Sri Sai Dinesh Jaliparthi, Jiaxi Lu, Rithvik Akula, Mario Scala, Julian F. Niedermair, Nikolaus Stranger, Sebastian Tschauner, Georg M. Schmölzer, Maria Jose Veloza Vega, Juan Sebastián Osorio Valencia, Oscar Jaramillo Robledo, Oscar Julian López Uribe, Saif Afat, Thomas Küstner, Soroosh Tayebi Arasteh, Daniel Truhn, Kelsey L. Pomykala, Jens Kleesiek, Naela Himayati Afifah, Rozan M. Irfan, Reza Shahriarirad, Amirhossein Erfani, Israel Amirav, Moria Be’er, Yasuhito Mitsuyama, Daiju Ueda, Alain S. Abi-Ghanem, Safaa Al Zakleet, Mossad Abdelhak Shaban Mohamed, Wan Irfan Bin W Mustapha, Naila Nizami, Rafeah Khan, Khalid Al-Kharazi, Zafar Iqbal, Abdullah Al Shahrani, Amna Kashgari, Tijana Prodanovic, Nikola Prodanovic, Desmond Shi Wei Lim, James Thomas Patrick Decourcy Hallinan, Phumza Nongena, Melissa Louise Cooke, Montserrat Bret-Zurita, Almudena Alonso-Ojembarrena, Alexandra Nemes, Yung-Chieh Lin, Wei-Ting Lin, Wen-Hui Fang, Chin Lin, Atchara Mahayosnond, Sira Sriswasdi, Piyapong Khumrin, Suphakris Tanmuk, Didem Arman, Serdar Cömert, Serdar Alan, Umit Ayse Tandircioglu, David Andrew Mong, Esther Chung, Michael Sadler, Morgan P. McBee, Richard H. Jones, and Pranav Rajpurkar

Nature Biomedical Engineering[URL]

Resolution-dependent self-supervised transfer in chest radiograph classification

Soroosh Tayebi Arasteh, Mina Shaigan, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, and Daniel Truhn

Communications Medicine[URL]

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

Mina Farajiamiri, Jeta Sopa, Saba Afza, Lisa Adams, Felix Barajas Ordonez, Tri-Thien Nguyen, Mahshad Lotfinia, Sebastian Wind, Keno Bressem, Sven Nebelung, Daniel Truhn, and Soroosh Tayebi Arasteh

Patterns, Cell Press[URL]

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

Sebastian Wind, Jeta Sopa, Laurin Schmid, Quirin Jackl, Sebastian Kiefer, Fei Wu, Martin Mayr, Harald Köstler, Gerhard Wellein, Andreas Maier, and Soroosh Tayebi Arasteh

Scientific Reports[URL]

When framing shapes the answer: cognitive bias and large language model reliability in radiology

Soroosh Tayebi Arasteh and Daniel Truhn

Radiology: Artificial Intelligence[URL]

A privacy stack for speech-based AI in digital health

Soroosh Tayebi Arasteh

npj Digital Public Health[URL]

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

Ismail Mese, Tugba Akinci D’Antonoli, Christian Bluethgen, ..., Soroosh Tayebi Arasteh, ..., Woojin Kim, and Burak Kocak

Diagnostic and Interventional Radiology[URL]

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

Marziyeh Mohammadi, Mohsen Vejdanihemmat, Mahshad Lotfinia, Mirabela Rusu, Daniel Truhn, Andreas Maier, and Soroosh Tayebi Arasteh

npj Digital Medicine[URL]

Differential privacy representation geometry for medical image analysis

Soroosh Tayebi Arasteh, Marziyeh Mohammadi, Sven Nebelung, and Daniel Truhn

MICCAI 2026[URL]

Automated evaluation of multi-turn dialogues in in-car conversational assistants

Vaishnav Negi, Lev Sorokin, Soroosh Tayebi Arasteh, and Andrea Stocco

IEEE International Conference on Intelligent Transportation Systems (ITSC) 2026[URL]

FRAME: separating sampling variation from performance disparities in medical image analysis

Mahshad Lotfinia, Daniel Truhn, Andreas Maier, and Soroosh Tayebi Arasteh

arXiv preprint[URL]

Automated feedback generation in paediatric simulation training: a prospective validation of AI-generated structured feedback reports

Mohamed Alhaskir, Hannah Haven, Michael Langner, Soroosh Tayebi Arasteh, Hauke Heidemeyer, Namir Sacic, Raphael W. Majeed, Anthea Peters, Nicole Müller, Mirka Fries, Ronny Otto, Kai O. Hensel, Christopher Plata, Tim Peters, Simon Ostermann, Yannik Haven, Miriam Hertwig, Jenny Unterkofler, Rainer Röhrig, and Jonas Bienzeisler

Research Square preprint[URL]

Medical foundation models converge less under label supervision

Soroosh Tayebi Arasteh, Sebastian Ziegelmayer, Mahshad Lotfinia, Lisa Adams, Sven Nebelung, Jakob Nikolas Kather, and Daniel Truhn

arXiv preprint[URL]

Vision-language models for chest radiography do not always need the image

Mahshad Lotfinia, Sebastian Ziegelmayer, Lisa Adams, Tri-Thien Nguyen, Daniel Truhn, Andreas Maier, and Soroosh Tayebi Arasteh

arXiv preprint[URL]

Safety and accuracy follow different scaling laws in clinical large language models

Sebastian Wind, Tri-Thien Nguyen, Jeta Sopa, Mahshad Lotfinia, Sebastian Bickelhaup, Michael Uder, Harald Köstler, Gerhard Wellein, Sven Nebelung, Daniel Truhn, Andreas Maier, and Soroosh Tayebi Arasteh

arXiv preprint[URL]

Case-grounded evidence verification: a framework for constructing evidence-sensitive supervision

Soroosh Tayebi Arasteh, Mehdi Joodaki, Mahshad Lotfinia, Sven Nebelung, and Daniel Truhn

arXiv preprint[URL]

The pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis

Soroosh Tayebi Arasteh, Mina Farajiamiri, Mahshad Lotfinia, Behrus Hinrichs-Puladi, Jonas Bienzeisler, Mohamed Alhaskir, Mirabela Rusu, Christiane Kuhl, Sven Nebelung, and Daniel Truhn

arXiv preprint[URL]

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

Sebastian Wind, Jeta Sopa, Daniel Truhn, Mahshad Lotfinia, Tri-Thien Nguyen, Keno Bressem, Lisa Adams, Mirabela Rusu, Harald Köstler, Gerhard Wellein, Andreas Maier, and Soroosh Tayebi Arasteh

npj Digital Medicine[URL]

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

Soroosh Tayebi Arasteh, Mahshad Lotfinia, Paula Andrea Perez-Toro, Tomas Arias-Vergara, Mahtab Ranji, Juan Rafael Orozco-Arroyave, Maria Schuster, Andreas Maier, and Seung Hee Yang

npj Artificial Intelligence[URL]

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

Lukas Buess, Matthias Keicher, Nassir Navab, Andreas Maier, and Soroosh Tayebi Arasteh

Biomedical Engineering Letters[URL]

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

Mahshad Lotfinia, Arash Tayebiarasteh, Samaneh Samiei, Mehdi Joodaki, and Soroosh Tayebi Arasteh

European Journal of Radiology Artificial Intelligence[URL]

RadioRAG: online retrieval-augmented generation for radiology question answering

Soroosh Tayebi Arasteh, Mahshad Lotfinia, Keno Bressem, Robert Siepmann, Lisa Adams, Dyke Ferber, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, and Daniel Truhn

Radiology: Artificial Intelligence[URL]

Accelerating breast MRI acquisition with generative AI models

Augustine Okolie, Timm Dirrichs, Luisa Charlotte Huck, Sven Nebelung, Soroosh Tayebi Arasteh, Teresa Nolte, Tianyu Han, Christiane Katharina Kuhl, and Daniel Truhn

European Radiology[URL]

Acoustic-driven generation of pathological speech reports using large language models

Tomas Arias-Vergara, Lukas Buess, Nastassia Vysotskaya, Soroosh Tayebi Arasteh, Juan Rafael Orozco-Arroyave, Maria Schuster, Elmar Noeth, Andreas Maier, and Paula Andrea Perez-Toro

Research Square preprint[URL]

Perceptual implications of automatic anonymization in pathological speech

Soroosh Tayebi Arasteh, Saba Afza, Tri-Thien Nguyen, Lukas Buess, Maryam Parvin, Tomas Arias-Vergara, Paula Andrea Perez-Toro, Hiu Ching Hung, Mahshad Lotfinia, Thomas Gorges, Elmar Noeth, Maria Schuster, Seung Hee Yang, and Andreas Maier

arXiv preprint[URL]

The treasure trove hidden in plain sight: the utility of GPT-4 in chest radiograph evaluation

Soroosh Tayebi Arasteh, Robert Siepmann, Marc Huppertz, Mahshad Lotfinia, Behrus Puladi, Christiane Kuhl, Daniel Truhn, and Sven Nebelung

Radiology[URL]

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

Soroosh Tayebi Arasteh, Tomás Arias-Vergara, Paula Andrea Pérez-Toro, Tobias Weise, Kai Packhäuser, Maria Schuster, Elmar Noeth, Andreas Maier, and Seung Hee Yang

Communications Medicine[URL]

Intraindividual comparison of different methods for automated BPE assessment at breast MRI: a call for standardization

Gustav Müller-Franzes, Firas Khader, Soroosh Tayebi Arasteh, Luisa Huck, Maike Bode, Tianyu Han, Teresa Lemainque, Jakob Nikolas Kather, Sven Nebelung, Christiane Kuhl, and Daniel Truhn

Radiology[URL]

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

Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, and Georgios Kaissis

Communications Medicine[URL]

Large language models streamline automated machine learning for clinical studies

Soroosh Tayebi Arasteh, Tianyu Han, Mahshad Lotfinia, Christiane Kuhl, Jakob Nikolas Kather, Daniel Truhn, and Sven Nebelung

Nature Communications[URL]

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

Soroosh Tayebi Arasteh, Leo Misera, Jakob Nikolas Kather, Daniel Truhn, and Sven Nebelung

European Radiology Experimental[URL]

Encrypted federated learning for secure decentralized collaboration in cancer image analysis

Daniel Truhn*, Soroosh Tayebi Arasteh*, et al.

Medical Image Analysis[URL]

Securing collaborative medical AI by using differential privacy: domain transfer for classification of chest radiographs

Soroosh Tayebi Arasteh, Mahshad Lotfinia, Teresa Nolte, Marwin-Jonathan Sähn, Peter Isfort, Christiane Kuhl, Sven Nebelung, Georgios Kaissis, and Daniel Truhn

Radiology: Artificial Intelligence[URL]

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

Soroosh Tayebi Arasteh, Christiane Kuhl, Marwin-Jonathan Saehn, Peter Isfort, Daniel Truhn, and Sven Nebelung

Scientific Reports[URL]

The effect of speech pathology on automatic speaker verification: a large-scale study

Soroosh Tayebi Arasteh, Tobias Weise, Maria Schuster, Elmar Noeth, Andreas Maier, and Seung Hee Yang

Scientific Reports[URL]

Automated segmentation of 3D cine cardiovascular magnetic resonance imaging

Soroosh Tayebi Arasteh, Jennifer Romanowicz, Danielle F. Pace, Polina Golland, Andrew J. Powell, Andreas K. Maier, Daniel Truhn, Tom Brosch, Juergen Weese, Mahshad Lotfinia, Rob J. van der Geest, and Mehdi H. Moghari

Frontiers in Cardiovascular Medicine[URL]

Multimodal deep learning for integrating chest radiographs and clinical parameters: a case for transformers

Firas Khader, Gustav Müller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh, Christoph Haarburger, Johannes Stegmaier, Keno Bressem, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, and Daniel Truhn

Radiology[URL]

Fibroglandular tissue segmentation in breast MRI using vision transformers: a multi-institutional evaluation

Gustav Müller-Franzes, Fritz Müller-Franzes, Luisa Huck, Vanessa Raaff, Eva Kemmer, Firas Khader, Soroosh Tayebi Arasteh, Teresa Lemainque, Jakob Nikolas Kather, Sven Nebelung, Christiane Kuhl, and Daniel Truhn

Scientific Reports[URL]

A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis

Gustav Müller-Franzes, Jan Moritz Niehues, Firas Khader, Soroosh Tayebi Arasteh, Christoph Haarburger, Christiane Kuhl, Tianci Wang, Tianyu Han, Teresa Nolte, Sven Nebelung, Jakob Nikolas Kather, and Daniel Truhn

Scientific Reports[URL]

Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data

Firas Khader, Jakob Nikolas Kather, Gustav Müller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh, Karim Hamesch, Keno Bressem, Christoph Haarburger, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, and Daniel Truhn

Scientific Reports[URL]

Denoising diffusion probabilistic models for 3D medical image generation

Firas Khader, Gustav Müller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baeßler, Sebastian Foersch, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, and Daniel Truhn

Scientific Reports[URL]

Collaborative training of medical artificial intelligence models with non-uniform labels

Soroosh Tayebi Arasteh, Peter Isfort, Marwin Saehn, Gustav Mueller-Franzes, Firas Khader, Jakob Nikolas Kather, Christiane Kuhl, Sven Nebelung, and Daniel Truhn

Scientific Reports[URL]

Using machine learning to reduce the need for contrast agents in breast MRI through synthetic images

Gustav Müller-Franzes, Luisa Huck, Soroosh Tayebi Arasteh, Firas Khader, Tianyu Han, Volkmar Schulz, Ebba Dethlefsen, Jakob Nikolas Kather, Sven Nebelung, Teresa Nolte, Christiane Kuhl, and Daniel Truhn

Radiology[URL]

Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages

Soroosh Tayebi Arasteh, Cristian David Ríos-Urrego, Elmar Nöth, Andreas Maier, Seung Hee Yang, Jan Rusz, and Juan Rafael Orozco-Arroyave

INTERSPEECH 2023[URL]

Vector-quantized latent flows for medical image synthesis and out-of-distribution detection

Firas Khader, Gustav Müller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Jakob Nikolas Kather, Johannes Stegmaier, Sven Nebelung, and Daniel Truhn

IEEE ISBI 2023[URL]

Conversion between cubic Bézier curves and Catmull-Rom splines

Soroosh Tayebi Arasteh and Adam Kalisz

SN Computer Science[URL]

How will your tweet be received? Predicting the sentiment polarity of tweet replies

Soroosh Tayebi Arasteh, Mehrpad Monajem, Vincent Christlein, Philipp Heinrich, Anguelos Nicolaou, Hamidreza Naderi Boldaji, Mahshad Lotfinia, and Stefan Evert

IEEE International Conference on Semantic Computing (ICSC) 2021[URL]

An empirical study on text-independent speaker verification based on the GE2E method

Soroosh Tayebi Arasteh

arXiv preprint[URL]