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Federate Learning and mUlti-party computation Techniques for prostatE cancer

Project description

DEENESFRITPL

Pioneering secure healthcare AI across borders

Healthcare data holds the key to groundbreaking discoveries, but privacy concerns have been a roadblock. Harnessing the potential of data-driven healthcare while preserving privacy and security is a challenge. The EU-funded FLUTE project addresses this by pioneering novel methods for cross-border data utilisation. FLUTE focuses on enhancing secure multi-party computation in federated learning, with advanced artificial intelligence (AI) models and secure execution environments. These innovations will form a privacy-focused platform for healthcare AI solutions development. FLUTE will integrate with health-data hubs across three countries, creating a powerful AI toolset for prostate cancer diagnosis. This multinational effort aims to improve predictions, reducing unnecessary procedures and cutting costs.

Objective

The FLUTE project will advance and scale up data-driven healthcare by developing novel methods for privacy-preserving cross-border utilization of data hubs. Advanced research will be performed to push the performance envelope of secure multi-party computation in Federated Learning, including the associated AI models and secure execution environments. The technical innovations will be integrated in a privacy-enforcing platform that will provide innovators with a provenly secure environment for federated healthcare AI solution development, testing and deployment, including the integration of real world health data from the data hubs and the generation and utilization of synthetic data. To maximize the impact, adoption and replicability of the results, the project will contribute to the global HL7 FHIR standard development, and create novel guidelines for GDPR-compliant cross-border Federated Learning in healthcare.
To demonstrate the practical use and impact of the results, the project will integrate the FLUTE platform with health data hubs located in three different countries, use their data to develop a novel federated AI toolset for diagnosis of clinically significant prostate cancer and perform a multi-national clinical validation of its efficacy, which will help to improve predictions of aggressive prostate cancer while avoiding unnecessary biopsies, thus improving the welfare of patients and significantly reducing the associated costs.
Team. The 11-strong consortium will include three clinical / data partners from three different countries, three technology SMEs, three technology research partners, a legal/ethics partner and a standards organization.
Collaboration. In accordance with the priorities set by the European Commission, the project will target collaboration, cross-fertilization and synergies with related national and international European projects.

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Call for proposal

HORIZON-HLTH-2022-IND-13

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Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

Coordinator

INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE
Net EU contribution
€ 1 005 000,00
Address
DOMAINE DE VOLUCEAU ROCQUENCOURT
78153 Le Chesnay Cedex
France

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Region
Ile-de-France Ile-de-France Yvelines
Activity type
Research Organisations
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Total cost
€ 1 005 000,00

Participants (9)

Partners (1)

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Last update: 13 July 2023

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Permalink: https://cordis.europa.eu/project/id/101095382

European Union, 2024