@inbook{b1835cdeab574c22a61e183e9c50edb5,
title = "Privacy-Preserving AI in Healthcare",
abstract = "Recent advances in Artificial Intelligence promise a brighter future for many industries. Particularly, in healthcare, AI is now playing a central role to complement understanding of the current problems while paving the way for new discoveries. However, as AI is fueled by data, serious concerns are rising to keep the balance between expanding AI and preserving the privacy of the data it utilizes, which, in the case of healthcare, often contains personal and sensitive information. In this chapter, we shed some light on how to preserve the privacy of data in healthcare while still harnessing and optimizing AI. We discuss several technical solutions that enable AI to advance while preserving the privacy of the underlying data. We also discuss privacy from a legal point of view and show how traditional legislation may fail to provide adequate protection to health data, then discuss more recent legislations with promising approach to achieving adequate data privacy.",
keywords = "AI, Health data, Healthcare, Privacy, Privacy-preserving",
author = "Saif Al-Kuwari",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.",
year = "2021",
doi = "10.1007/978-3-030-67303-1_6",
language = "English",
series = "Lecture Notes in Bioengineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "65--77",
booktitle = "Lecture Notes in Bioengineering",
address = "Germany",
}