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GRANITE

Financiado

Integrated AI Diagnostics in Breast Cancer

In EU-27, it is estimated that >355,000 were diagnosed with breast cancer (BC) in 2020. Initiatives to reduce this burden in Europe involve early and precise diagnosis in the standard-of-care management to decrease unnecessary or... ver más

01/09/2026

UCY

164K€

Presupuesto del proyecto: 164K€

Líder del proyecto

UNIVERSITY OF CYPRUS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 3 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-03-13

HORIZON-MSCA-2023-PF-01-01: MSCA Postdoctoral Fellowships 2023 ExpectedOutcome:Project results are expected to contribute to the following outcomes:

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

3 Participantes

UCY

164.33K€ | Lider

INRIA

N.D. | Participante

ASTRAZENECA AB

N.D. | Participante

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Duración del proyecto: 29 meses Fecha Inicio: 2024-03-13
Fecha Fin: 2026-09-01

Líder del proyecto

UNIVERSITY OF CYPRUS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 164K€

Descripción del proyecto In EU-27, it is estimated that >355,000 were diagnosed with breast cancer (BC) in 2020. Initiatives to reduce this burden in Europe involve early and precise diagnosis in the standard-of-care management to decrease unnecessary or insufficient treatment. Notably, precision medicine in BC is still in its infancy and is becoming even more critical with neoadjuvant chemotherapy (NAC), a standard of care treatment protocol in HER2-positive (HER2+) and triple negative (TN) subtypes. Recently, the use of digital diagnostics with AI is gaining momentum since it shows great promise towards accelerating personalized BC patients’ pre- and post-NAC predictions. While AI paves the way to next generation diagnostics, this has yet from been translated as a) it mostly operates in single data modalities that fail to capture the complex disease alterations, b) integrated AI usually suffers from data incompleteness usually leading to models trained with limited data that fail to generalize to new patients and/or that are not able to integrate partially observed multimodal information from the whole population. GRANITE focuses to address these unmet needs and goes beyond the state of the art, fusing the most relevant standard of care data (radiology, pathology, clinical, demographic), leveraging novel AI and state-of-the-art image analysis (radiomics) based on the extensive previous work of the experienced researcher (ER). GRANITE will deploy pre-trained DL models from the ER and fine-tuned, technically validated and clinically evaluated using more than 150 non-metastatic BC cases from the Bank of Cyprus Oncology Centre (BoCOC). ER’s participation in the AI4HI project will help transcend FUTURE-AI guidelines (Fairness, Universality, Traceability, Usability, Robustness and Explainability; future-ai.eu) into GRANITE to generate real-world evidence and make our AI clinically sound, ethically aware and technically applicable, and to promote AI trust and and acceptance in BC management.

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