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

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

3 February 2023

Soroosh Tayebi Arasteh

Alexander Ziller

Christiane Kuhl

Marcus R. Makowski

Daniel Rueckert

Daniel Truhn

Georgios Kaissis

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

12 / 12 papers shown

Title
Perceptual Implications of Automatic Anonymization in Pathological Speech Soroosh Tayebi Arasteh Saba Afza Tri-Thien Nguyen Lukas Buess Maryam Parvin ... Thomas Gorges E. Noeth Maria Schuster S. Yang Andreas K. Maier 22 0 0 01 May 2025
Boosting multi-demographic federated learning for chest x-ray analysis using general-purpose self-supervised representations Mahshad Lotfinia Arash Tayebiarasteh Samaneh Samiei Mehdi Joodaki Soroosh Tayebi Arasteh 28 0 0 11 Apr 2025
The Impact of Speech Anonymization on Pathology and Its Limits Soroosh Tayebi Arasteh T. Arias-Vergara Paula Andrea Pérez-Toro Tobias Weise Kai Packhaeuser Maria Schuster E. Noeth Andreas K. Maier Seung Hee Yang 36 2 0 11 Apr 2024
Unlocking Accuracy and Fairness in Differentially Private Image Classification Leonard Berrada Soham De J. Shen Jamie Hayes Robert Stanforth David Stutz Pushmeet Kohli Samuel L. Smith Borja Balle 19 13 0 21 Aug 2023
Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images Soroosh Tayebi Arasteh Leo Misera Jakob Nikolas Kather Daniel Truhn S. Nebelung 23 8 0 15 Aug 2023
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 T. Nolte Marwin Saehn P. Isfort Christiane Kuhl S. Nebelung Georgios Kaissis Daniel Truhn MedIm 11 8 0 10 Jun 2023
Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages Soroosh Tayebi Arasteh C. D. Ríos-Urrego E. Noeth Andreas K. Maier Seung Hee Yang J. Rusz J. Orozco-Arroyave FedML 23 13 0 18 May 2023
GARDNet: Robust Multi-View Network for Glaucoma Classification in Color Fundus Images Ahmed Al Mahrooqi Dmitrii Medvedev Rand Muhtaseb Mohammad Yaqub 25 6 0 25 May 2022
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 64 181 0 06 Dec 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 144 348 0 25 Sep 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,187 0 23 Aug 2019
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,237 0 25 Aug 2016