A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf
.
Secure and Robust Machine Learning for Healthcare: A Survey
2020
IEEE Reviews in Biomedical Engineering
Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart signals to computer-aided diagnosis (CADx) using multi-dimensional medical images. Notwithstanding the impressive performance of ML/DL, there are still lingering doubts regarding the robustness of ML/DL in healthcare settings (which is
doi:10.1109/rbme.2020.3013489
pmid:32746371
fatcat:wd2flezcjng4jjsn46t24c5yb4