(Neuroimaging Federated Learning Analysis for Multi-site Environments) is a decentralized platform for running computations across multiple sites while preserving data privacy. Its modular design, scalability, and ease of use make it a powerful tool for collaborative research in neuroimaging and other fields.

Key Features

Modular Architecture: Built to support a wide range of use cases, NeuroFLAME’s modular infrastructure allows for easy expansion and customization.

Flexibility: Suitable for various research needs, from single-site studies to multi-site collaborations.

Reliability: A focus on ensuring smooth operation across diverse environments, with clear error handling and logging.

User-Friendly Interface: Designed for ease of use, allowing researchers to focus on their work without unnecessary complexity.

Reproducibility: Study configurations are captured and preserved, ensuring results can be easily replicated.

Transparency and Control: Users have full visibility into their computations, inputs, and results.