Objective
Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer, yet it remains underrepresented in clinical trials due to its distinct clinical course and metastatic behavior. Radiological detection of ILC is particularly challenging, as lesions often present with low contrast and diffuse infiltration. In pathology, overlapping morphological features between classic and non-classic ILC and other breast cancer subtypes lead to diagnostic uncertainty and high inter-pathologist variability. These limitations extend to molecular assays and AI models, which have largely been trained on cohorts with low ILC representation and typically underperform for this subtype. M4GIC-ILC—a Multi-modal, Multi-site, Multi-omic, Multi-AGent AI framework for the clinical management of ILC—addresses these challenges by unifying representation learning, generative AI, and supervised prediction across pathology, radiology, molecular, and clinical data. Foundation-model backbones are fine-tuned for ILC to learn batch-aware, biologically grounded embeddings, while generative AI provides calibrated proxies for missing modalities (virtual IHC, virtual MGS, and imaging views), enabling clinicians to interpret cases in familiar diagnostic settings. On top, task-specific predictors estimate diagnosis (ILC vs other; classic vs non-classic), staging (T/N, focality, laterality), relapse risk, and treatment benefit (endocrine, CDK4/6i, chemotherapy), with calibrated uncertainty and abstention when confidence is low. The framework is orchestrated by a multi-agent system that integrates these tools into interactive, natural-language reports with visual explanations and full provenance. Development and validation occur through federated learning on a harmonized, FAIR multisite repository. M4GIC-ILC will bridge the current diagnostic and therapeutic gap in ILC, delivering trustworthy, explainable AI that improves patient stratification and personalizes breast cancer care.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-EIC - HORIZON EIC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIC-2025-PATHFINDERCHALLENGES-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3000 Leuven
Belgium
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.