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This paper is an overview of the EU-funded project TRUMPET (https://trumpetproject.eu/), and gives an outline of its scope and main technical aspects and objectives. In recent years, Federated Learning has emerged as a revolutionary privacy-enhancing technology. However, further research has cast a shadow of doubt on its strength for privacy protection. The goal of TRUMPET is to research and develop novel privacy enhancement methods for Federated Learning, and to deliver a highly scalable Federated AI service platform for researchers, that will enable AI-powered studies of siloed, multi-site, crossdomain, cross-border European datasets with privacy guarantees that follow the requirements of GDPR. The generic TRUMPET platform will be piloted, demonstrated and validated in the specific use case of European cancer hospitals, allowing researchers and policymakers to extract AI-driven insights from previously inaccessible cross-border, cross-organization cancer data, while ensuring the patients’ privacy
Sciences informatiques, General data protection regulations, Multi-site, Computer Networks and Communications, Clinical cancer research, Federated learning, Cancer research, [INFO] Computer Science [cs], Privacy Enhancing Technologies, Ingénierie, informatique & technologie, Patient Data Privacy, Artificial Intelligence, Federated Learning Privacy Metrics Privacy Enhancing Technologies General Data Protection Regulation Clinical Cancer Research Patient Data Privacy, Patient data privacy, Safety, Risk, Reliability and Quality, Privacy Metrics, Healthcare, Cross-border, Clinical Cancer Research, Computer science, Engineering, computing & technology, Patient data, AI, Privacy metric, Privacy enhancing technologies, Federated Learning, Information Systems, General Data Protection Regulation
Sciences informatiques, General data protection regulations, Multi-site, Computer Networks and Communications, Clinical cancer research, Federated learning, Cancer research, [INFO] Computer Science [cs], Privacy Enhancing Technologies, Ingénierie, informatique & technologie, Patient Data Privacy, Artificial Intelligence, Federated Learning Privacy Metrics Privacy Enhancing Technologies General Data Protection Regulation Clinical Cancer Research Patient Data Privacy, Patient data privacy, Safety, Risk, Reliability and Quality, Privacy Metrics, Healthcare, Cross-border, Clinical Cancer Research, Computer science, Engineering, computing & technology, Patient data, AI, Privacy metric, Privacy enhancing technologies, Federated Learning, Information Systems, General Data Protection Regulation
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