The FeatureCloud Platform for Federated Learning in Biomedicine: Unified Approach.

ABSTRACT:

Background

Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distributed machine learning models without sharing sensitive data. In addition, the implementation is time-consuming and requires advanced programming skills and complex technical infrastructures.

Objective

Various tools and frameworks have been developed to simplify the development of FL algorithms and provide the necessary technical infrastructure. Although there are many high-quality frameworks, most focus only on a single application

SUBMITTER: Matschinske J 

PROVIDER: S-EPMC10372562 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature