Abstract Upon the General Data Protection Regulation's (GDPR) application on 25 May
2018 across the European Union, new legal requirements for the protection of personal data …

Medical vision-language models (VLMs) combine computer vision (CV) and natural
language processing (NLP) to analyze visual and textual medical data. Our paper reviews …

Deep learning techniques based on neural networks have shown significant success in a
wide range of AI tasks. Large-scale training datasets are one of the critical factors for their …

The federal statistical system is experiencing competing pressures for change. On the one
hand, for confidentiality reasons, much socially valuable data currently held by federal …

It is a well-known fact that the progress of personal communication devices leads to serious
concerns about privacy in general, and location privacy in particular. As a response to these …

Privacy protection is paramount in conducting health research. However, studies often rely
on data stored in a centralized repository, where analysis is done with full access to the …

Learning problems form an important category of computational tasks that generalizes many
of the computations researchers apply to large real-life data sets. We ask, What concept …

The use of formal privacy to protect the confidentiality of responses in the 2020 Decennial
Census of Population and Housing has triggered renewed interest and debate over how to …

Health big data has already been the most important big data for its serious privacy
disclosure concerns and huge potential value of secondary use. Measurements must be …

Federated learning has received a great deal of research attention recently, with privacy
protection becoming a key factor in the development of artificial intelligence. Federated …