Documenting the de-identification process of clinical and imaging data for AI for health imaging projects.

ABSTRACT: Artificial intelligence (AI) is revolutionizing the field of medical imaging, holding the potential to shift medicine from a reactive "sick-care" approach to a proactive focus on healthcare and prevention. The successful development of AI in this domain relies on access to large, comprehensive, and standardized real-world datasets that accurately represent diverse populations and diseases. However, images and data are sensitive, and as such, before using them in any way the data needs to be modified to protect the privacy of the patients. This paper explores the approaches in the domain of five EU projects working on the creation of ethically compliant and GDPR-regulated European medical imaging platforms, focused on cancer-related data. It presents the individual approaches to the de-iden

SUBMITTER: Kondylakis H 

PROVIDER: S-EPMC11139818 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature