Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review.

ABSTRACT:

Background

The collection, storage, and analysis of large data sets are relevant in many sectors. Especially in the medical field, the processing of patient data promises great progress in personalized health care. However, it is strictly regulated, such as by the General Data Protection Regulation (GDPR). These regulations mandate strict data security and data protection and, thus, create major challenges for collecting and using large data sets. Technologies such as federated learning (FL), especially paired with differential privacy (DP) and secure multiparty computation (SMPC), aim to solve these challenges.

Objective

This scoping review aimed to summarize the current discussion on the legal questions and concerns related to FL systems in medical research. We were partic

SUBMITTER: Brauneck A 

PROVIDER: S-EPMC10131784 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature