Preserve data privacy, enhance AI research in healthcare.
TRUMPET project ended in December 31st , 2025
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The aim of TRUMPET project is to develop a platform based on Armoured Federated Learning
for researchers and solution developers.
The platform developed by TRUMPET consortium will enable solution developers to create tools for healthcare professionals that allow them
to analyze their own patient data and compare it with data from other hospitals and research centers while maintaining
patient privacy and anonymity in accordance with GDPR European policy.
SCIENTIFIC IMPACT
Increase protection in Federated Learning for its proliferation in scientific community
Identify specific privacy threats related to Federated Learning
Create novel metrics for measuring privacy compliance and develop tools for automated measurement of privacy in Federated Learning
Perform a legal study on GDPR implication in Federated learning
SOCIETAL IMPACT
Identify and evaluate specific needs of data user for Federated Learning improving
Contribute to EU policy making processes on Cybersecurity and GDPR compliance
Give a safe access to patient data keeping them protected and anonymous
Rise the interest of citizen on diagnosis and therapies AI-based
ECONOMIC IMPACT
Attract software houses that are interested in the application of TRUMPET platform
Present to other data providers the opportunity of TRUMPET platform
Explore the utilization of TRUMPET platform in diverse fields.
5 reasons for promoting the use
of federated learning by TRUMPET project
Federated learning can improve the accuracy of medical predictions and diagnoses by training models on a larger and more diverse dataset
By keeping patient data on the device, federated learning enables healthcare organizations to comply with strict privacy regulations and protect sensitive information
Federated learning can facilitate the development of AI models for use in remote or low-resource areas, providing access to life-saving technologies for patients in need
The decentralized nature of federated learning allows for the collaboration of healthcare providers and researchers from around the world, leading to faster advancements in medical research and treatment
Federated learning can help healthcare organizations achieve their goals of providing personalized and effective care for their patients, improving overall health outcomes
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