Secure and Robust Machine Learning for Healthcare: A Survey

Adnan Qayyum; Junaid Qadir; Muhammad Bilal; Ala Al-Fuqaha

doi:10.1109/RBME.2020.3013489

Secure and Robust Machine Learning for Healthcare: A Survey

Adnan Qayyum
, Junaid Qadir
, Muhammad Bilal
, Ala Al-Fuqaha^*

^*Corresponding author for this work

Information Technology University
University of the West of England
Hamad bin Khalifa University

Research output: Contribution to journal › Review article › peer-review

456 Citations (SciVal)

Original language	English
Article number	9153891
Pages (from-to)	156-180
Number of pages	25
Journal	IEEE Reviews in Biomedical Engineering
Volume	14
DOIs	https://doi.org/10.1109/RBME.2020.3013489
Publication status	Published (VoR) - 2021

Funding

Manuscript received January 28, 2020; revised June 6, 2020; accepted July 9, 2020. Date of publication July 31, 2020; date of current version January 22, 2021. This work was supported by Qatar National Library (QNL). The statements made herein are solely the responsibility of the authors. (Corresponding author: Ala Al-Fuqaha.) Adnan Qayyum and Junaid Qadir are with the Information Technology University, Lahore 54000, Pakistan (e-mail: [email protected]; [email protected]).

Funders
Qatar National Library

Keywords

Adversarial ML
healthcare
privacy preserving ML
robust ML
secure ML

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10.1109/RBME.2020.3013489

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Secure and Robust Machine Learning for Healthcare: A Survey

Funding

Keywords

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