Benchmarking Differentially Private Residual Networks for Medical Imagery

Privacy preserving integration of health care data

Adam, N., White, T., Shafiq, B., Vaidya, J., and He, X · 2007

Earlier work this paper cites.

Towards a framework for privacy preserving medical data mining based on standard medical classifications

Faravelon, A. and Verdier, C · 2010

Earlier work this paper cites.

What can we learn privately?

Kasiviswanathan, S. P., Lee, H. K., Nissim, K., Raskhodnikova, S., and Smith, A · 2011

Earlier work this paper cites.

Practicing differential privacy in health care: A review

Dankar, F. K. and El Emam, K · 2013

Earlier work this paper cites.

The algorithmic foundations of differential privacy

Dwork, C., Roth, A., et al · 2014

Earlier work this paper cites.

Very deep convolutional networks for large-scale image recognition

Original

Simonyan, K. and Zisserman, A · 2014

Earlier work this paper cites.

Deep learning with differential privacy

Abadi, M., Chu, A., Goodfellow, I., McMahan, H. B., Mironov, I., Talwar, K., and Zhang, L · 2016

Earlier work this paper cites.

Deep residual learning for image recognition

He, K., Zhang, X., Ren, S., and Sun, J · 2016

Earlier work this paper cites.

Inception-v4, inception-resnet and the impact of residual connections on learning

Szegedy, C., Ioffe, S., Vanhoucke, V., and Alemi, A. A · 2017

Cited alongside, same era.

Private machine learning in tensorflow using secure computation

Original

Dahl, M., Mancuso, J., Dupis, Y., Decoste, B., Giraud, M., Livingstone, I., Patriquin, J., and Uhma, G · 2018

Cited alongside, same era.

Identifying medical diagnoses and treatable diseases by image-based deep learning

Kermany, D. S., Goldbaum, M., Cai, W., Valentim, C. C., Liang, H., Baxter, S. L., McKeown, A., Yang, G., Wu, X., Yan, F., et al · 2018

Cited alongside, same era.

Privacy-preserving aggregation of personal health data streams

Kim, J. W., Jang, B., and Yoo, H · 2018

Cited alongside, same era.

A generic framework for privacy preserving deep learning. arxiv 2018

Original

Ryffel, T., Trask, A., Dahl, M., Wagner, B., Mancuso, J., Rueckert, D., and Passerat-Palmbach, J · 2018

Aptos 2019 diabetic retinopathy dataset

Hospital, A. E · 2019

Later among the works it cites.

Blockchain-based privacy-preserving healthcare architecture

Hossein, K. M., Esmaeili, M. E., Dargahi, T., and khonsari, A · 2019

Later among the works it cites.

Technical report, Centers for Disease Control and Prevention(CDC), 2020

Covidview week 13 · 2020

Closest in time.

Secure, privacy-preserving and federated machine learning in medical imaging

Kaissis, G. A., Makowski, M. R., Rückert, D., and Braren, R. F · 2020

Closest in time.

A principled approach to learning stochastic representations for privacy in deep neural inference

Original

Mireshghallah, F., Taram, M., Jalali, A., Elthakeb, A. T., Tullsen, D., and Esmaeilzadeh, H · 2020

Closest in time.

Privacy in deep learning: A survey