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Open Consortium for Decentralized Medical Artificial Intelligence

Project description

DEENESFRITPL

Swarm learning software for AI-powered cancer screening

Artificial intelligence (Al) will revolutionise healthcare by improving medical diagnosis. This requires large collections of patient data to be shared, which often faces several obstacles. Swarm learning (SL) allows for privacy-conserving development of medical AI, but access to SL has been limited. In this context, the EU-funded ODELIA project will build the first open-source software framework for SL, providing streamlined development of Al solutions which will be applied in cancer screening. In addition to delivering a useful medical application for breast cancer screening, the project will demonstrate the clinical benefit of SL in terms of accelerated development, increased performance and robust generalisability to ultimately save thousands of lives.

Objective

ArtifArtificial Intelligence (AI) will revolutionize healthcare as its diagnostic performance approaches that of clinical experts. In particular, in cancer screening, AI helps patients to make better-informed decisions and reduce medical error. However, this requires large datasets whose collection faces severe practical, ethical and legal obstacles. These obstacles can be overcome with swarm learning (SL) where partners jointly train AI models without sharing any data. Yet, access to SL technology is seriously limited because no studies have implemented SL in a true multinational setup, no practically usable implementation of SL is available, researchers & healthcare providers have no experience with setting up SL networks and policymakers are currently unaware of the broader implications of SL. ODELIA will address & solve these issues: ODELIA will build the first open-source software framework for SL, providing an assembly line for the streamlined development of AI solutions. To serve as a blueprint for future SL-based AI systems, ODELIA partners collaborate as a swarm to develop the first clinically useful AI algorithm for the detection of breast cancer in magnetic resonance imaging (MRI). The size of ODELIA's distributed database will exceed all previous studies and ODELIA's AI models will reach expert-level performance for breast cancer screening. Thereby, ODELIA will not only deliver a useful medical application, but prove the clinical benefit of SL in terms of accelerated development, increased performance and robust generalizability to ultimately save thousands of lives of European patients. ODELIA's success will push partners to serve as nuclei for the exponential growth of the SL network and extend SL to a multitude of medical applications. Thus, patients, healthcare providers and citizens in Europe will be provided with a digital infrastructure that enables development of expert-level AI tools on big data without compromising data safety and data privacy.

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Call for proposal

HORIZON-HLTH-2021-CARE-05

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Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

Coordinator

EIBIR GEMEINNUTZIGE GMBH ZUR FORDERUNG DER ERFORSCHUNG DER BIOMEDIZINISCHEN BILDGEBUNG
Net EU contribution
€ 719 624,50
Address
AM GESTADE 1
1010 Wien
Austria

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Region
Ostösterreich Wien Wien
Activity type
Research Organisations
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Total cost
€ 719 624,50

Participants (9)

Partners (2)

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Last update: 25 November 2022

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Permalink: https://cordis.europa.eu/project/id/101057091

European Union, 2024