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Private, fair and accurate: Training large-scale, privacy-preserving AI
models in medical imaging

v1v2v3v4v5 (latest)

Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging

Communications Medicine (Commun Med), 2023

3 February 2023

Soroosh Tayebi Arasteh

Alexander Ziller

Christiane Kuhl

Marcus R. Makowski

Daniel Rueckert

Daniel Truhn

Georgios Kaissis

ArXiv (abs)PDF HTML Github

Papers citing "Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging"

11 / 11 papers shown

Resolution scaling governs DINOv3 transfer performance in chest radiograph classification

Resolution scaling governs DINOv3 transfer performance in chest radiograph classification

Soroosh Tayebi Arasteh

Christiane Kuhl

Jakob Nikolas Kather

285

2

0

24 Dec 2025

Effect of Reporting Mode and Clinical Experience on Radiologists' Gaze and Image Analysis Behavior in Chest Radiography

Effect of Reporting Mode and Clinical Experience on Radiologists' Gaze and Image Analysis Behavior in Chest Radiography

Marc Sebastian von der Stueck

Felix Barajas Ordonez

Anca-Maria Iancu

...

Daniel Pinto dos Santos

Christiane Kuhl

87

0

0

17 Oct 2025

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

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

Marziyeh Mohammadi

Mohsen Vejdanihemmat

Mahshad Lotfinia

Andreas K. Maier

Soroosh Tayebi Arasteh

374

1

0

31 May 2025

Perceptual Implications of Automatic Anonymization in Pathological Speech

Perceptual Implications of Automatic Anonymization in Pathological Speech

Soroosh Tayebi Arasteh

Tri-Thien Nguyen

...

Andreas K. Maier

229

0

0

01 May 2025

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

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

Mahshad Lotfinia

Arash Tayebiarasteh

Soroosh Tayebi Arasteh

432

0

0

11 Apr 2025

SoK: What Makes Private Learning Unfair?

SoK: What Makes Private Learning Unfair?

276

1

0

24 Jan 2025

The Impact of Speech Anonymization on Pathology and Its Limits

The Impact of Speech Anonymization on Pathology and Its Limits

Soroosh Tayebi Arasteh

T. Arias-Vergara

Paula Andrea Pérez-Toro

Kai Packhaeuser

389

23

0

11 Apr 2024

Unlocking Accuracy and Fairness in Differentially Private Image
Classification

Unlocking Accuracy and Fairness in Differentially Private Image Classification

Leonard Berrada

Robert Stanforth

Samuel L. Smith

269

22

0

21 Aug 2023

Enhancing Network Initialization for Medical AI Models Using
Large-Scale, Unlabeled Natural Images

Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural ImagesEuropean Radiology Experimental (Eur Radiol Exp), 2023

Soroosh Tayebi Arasteh

Jakob Nikolas Kather

Daniel Truhn

434

25

0

15 Aug 2023

Preserving privacy in domain transfer of medical AI models comes at no
performance costs: The integral role of differential privacy

Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy

Soroosh Tayebi Arasteh

Mahshad Lotfinia

Christiane Kuhl

Georgios Kaissis

Daniel Truhn

286

13

0

10 Jun 2023

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

Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languagesInterspeech (Interspeech), 2023

Soroosh Tayebi Arasteh

C. D. Ríos-Urrego

Andreas K. Maier

J. Orozco-Arroyave

320

21

0

18 May 2023

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