The project aims to revolutionize healthcare collaboration by securely pooling medical imaging, billing, and patient outcomes data across different organizations without compromising privacy. Leveraging confidential computing and federated learning, it establishes a protected environment for data analysis. By processing data within secure enclaves and employing decentralized machine learning, the initiative ensures that sensitive information remains within its original location, safeguarding patient confidentiality. This innovative approach enables healthcare entities to collectively enhance patient care and operational efficiency, setting a new standard for privacy-preserving data analysis in the healthcare industry.