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Artificial intelligence (AI) models are increasingly used in the medical domain.
Robust de-anonymization of large sparse datasets
Arvind Narayanan and Vitaly Shmatikov · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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A statistical framework for differential privacy
Larry Wasserman and Shuheng Zhou · 2010
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Three naive bayes approaches for discrimination-free classification
Toon Calders and Sicco Verwer · 2010
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A firm foundation for private data analysis
Cynthia Dwork · 2011
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The algorithmic foundations of differential privacy
Cynthia Dwork, Aaron Roth, et al · 2014
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Bootstrapping and permuting paired t-test type statistics
Frank Konietschke and Markus Pauly · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Federated optimization: Distributed machine learning for on-device intelligence
Jakub Konečnỳ, H Brendan McMahan, Daniel Ramage, and Peter Richtárik · 2016
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Federated learning: Strategies for improving communication efficiency
Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016
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Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Incorporating nesterov momentum into adam
Timothy Dozat · 2016
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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas · 2017
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Defining an optimal cut-point value in roc analysis: an alternative approach
Ilker Unal · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q. Weinberger · 2017
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Group normalization
Yuxin Wu and Kaiming He · 2018
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Deep learning using rectified linear units (relu)
Abien Fred Agarap · 2018
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On the compatibility of privacy and fairness
Rachel Cummings, Varun Gupta, Dhamma Kimpara, and Jamie Morgenstern · 2019
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Differential privacy has disparate impact on model accuracy
Eugene Bagdasaryan, Omid Poursaeed, and Vitaly Shmatikov · 2019
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Privacy-preserving federated brain tumour segmentation
Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M Jorge Cardoso, et al · 2019
Cited alongside, same era.
Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports
Alistair EW Johnson, Tom J Pollard, Seth J Berkowitz, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Roger G Mark, and Steven Horng · 2019
Cited alongside, same era.
Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs
Alistair EW Johnson, Tom J Pollard, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Yifan Peng, Zhiyong Lu, Roger G Mark, Seth J Berkowitz, and Steven Horng · 2019
Cited alongside, same era.
Mish: A self regularized non-monotonic activation function
Diganta Misra · 2019
Cited alongside, same era.
Efficientnet: Rethinking model scaling for convolutional neural networks
Gaussian differential privacy
Jinshuo Dong, Aaron Roth, and Weijie J Su · 2022
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Reconstructing training data with informed adversaries
Borja Balle, Giovanni Cherubin, and Jamie Hayes · 2022
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Attacks on deidentification’s defenses
Aloni Cohen · 2022
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Unlocking high-accuracy differentially private image classification through scale
Soham De, Leonard Berrada, Jamie Hayes, Samuel L Smith, and Borja Balle · 2022
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Toward training at imagenet scale with differential privacy
Alexey Kurakin, Steve Chien, Shuang Song, Roxana Geambasu, Andreas Terzis, and Abhradeep Thakurta · 2022
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Mingxing Tan and Quoc Le · 2019
Cited alongside, same era.
Towards formalizing the gdpr’s notion of singling out
Aloni Cohen and Kobbi Nissim · 2020
Cited alongside, same era.
Neither private nor fair: Impact of data imbalance on utility and fairness in differential privacy
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, and Andrew Trask · 2020
Cited alongside, same era.
Comparison of chest radiograph interpretations by artificial intelligence algorithm vs radiology residents
Joy T Wu, Ken CL Wong, Yaniv Gur, Nadeem Ansari, Alexandros Karargyris, Arjun Sharma, Michael Morris, Babak Saboury, Hassan Ahmad, Orest Boyko, et al · 2020
Cited alongside, same era.
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning
Dmitrii Usynin, Alexander Ziller, Marcus Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, and Jonathan Passerat-Palmbach · 2021
Cited alongside, same era.
When the curious abandon honesty: Federated learning is not private
Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, and Nicolas Papernot · 2021
Cited alongside, same era.
Robbing the fed: Directly obtaining private data in federated learning with modified models
Liam Fowl, Jonas Geiping, Wojtek Czaja, Micah Goldblum, and Tom Goldstein · 2021
Cited alongside, same era.
Variational model inversion attacks
Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, and Alireza Makhzani · 2021
Cited alongside, same era.
Deep learning-based patient re-identification is able to exploit the biometric nature of medical chest x-ray data
Kai Packhäuser, Sebastian Gündel, Nicolas Münster, Christopher Syben, Vincent Christlein, and Andreas Maier · 2022
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Defending against reconstruction attacks through differentially private federated learning for classification of heterogeneous chest x-ray data
Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz, Axel Saalbach, and Bert Arnrich · 2022
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Artificial intelligence for clinical interpretation of bedside chest radiographs
Firas Khader, Tianyu Han, Gustav Müller-Franzes, Luisa Huck, Philipp Schad, Sebastian Keil, Emona Barzakova, Maximilian Schulze-Hagen, Federico Pedersoli, Volkmar Schulz, et al · 2022
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Differentially private training of residual networks with scale normalisation
Helena Klause, Alexander Ziller, Daniel Rueckert, Kerstin Hammernik, and Georgios Kaissis · 2022
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Elevating fundoscopic evaluation to expert level - automatic glaucoma detection using data from the airogs challenge
Firas Khader, Christoph Haarburger, Jörg-Christian Kirr, Marcel Menke, Jakob Nikolas Kather, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, and Daniel Truhn · 2022
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Gardnet: Robust multi-view network for glaucoma classification in color fundus images
Ahmed Al-Mahrooqi, Dmitrii Medvedev, Rand Muhtaseb, and Mohammad Yaqub · 2022
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Extracting training data from diffusion models
Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramer, Borja Balle, Daphne Ippolito, and Eric Wallace · 2023
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Georgios Kaissis, Jamie Hayes, Alexander Ziller, and Daniel Rueckert · 2023
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Tight auditing of differentially private machine learning
Milad Nasr, Jamie Hayes, Thomas Steinke, Borja Balle, Florian Tramèr, Matthew Jagielski, Nicholas Carlini, and Andreas Terzis · 2023
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Bounding training data reconstruction in dp-sgd
Jamie Hayes, Saeed Mahloujifar, and Borja Balle · 2023
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Do gradient inversion attacks make federated learning unsafe?
Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G Flores, Jan Kautz, Daguang Xu, et al · 2023
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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 · 2023
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Soroosh Tayebi Arasteh, Mahshad Lotfinia, Teresa Nolte, Marwin Saehn, Peter Isfort, Christiane Kuhl, Sven Nebelung, Georgios Kaissis, and Daniel Truhn · 2023
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Airogs: Artificial intelligence for robust glaucoma screening challenge
Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard, He Wang, Hongyi Sun, Firas Khader, Daniel Truhn, Temirgali Aimyshev, Yerkebulan Zhanibekuly, Tien-Dung Le, Adrian Galdran, Miguel Ángel González Ballester, Gustavo Carneiro, Devika R G, Hrishikesh P S, Densen Puthussery, Hong Liu, Zekang Yang, Satoshi Kondo, Satoshi Kasai, Edward Wang, Ashritha Durvasula, Jónathan Heras, Miguel Ángel Zapata, Teresa Araújo, Guilherme Aresta, Hrvoje Bogunović, Mustafa Arikan, Yeong Chan Lee, Hyun Bin Cho, Yoon Ho Choi, Abdul Qayyum, Imran Razzak, Bram van Ginneken, Hans G. Lemij, and Clara I. Sánchez · 2023
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