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INCISIVE

Financiado

Cerrado

A multimodal AI based toolbox and an interoperable health imaging repository for...

A multimodal AI based toolbox and an interoperable health imaging repository for the empowerment of imaging analysis related to the diagnosis prediction and follow up of cancer The increasing amount and availability of collected data (cancer imaging) and the development of novel technological tools based on Artificial Intelligence (AI) and Machine Learning (ML), provide unprecedented opportunities for be... ver más

31/03/2024

MAGGIOLI

10M€

Presupuesto del proyecto: 10M€

Líder del proyecto

MAGGIOLI SPA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 30 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-03-31

DT-TDS-05-2020: AI for Health Imaging Specific Challenge:Artificial Intelligence (AI) offers substantial opportunities for healthcare, sup...

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Características del participante

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

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

30 Participantes

MAGGIOLI

702.50K€ | Lider

INVELCO

150.25K€ | Participante

UNS

243.13K€ | Participante

VISARIS

299.50K€ | Participante

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Duración del proyecto: 46 meses Fecha Inicio: 2020-05-28
Fecha Fin: 2024-03-31

Líder del proyecto

MAGGIOLI SPA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 10M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The increasing amount and availability of collected data (cancer imaging) and the development of novel technological tools based on Artificial Intelligence (AI) and Machine Learning (ML), provide unprecedented opportunities for better cancer detection and classification, image optimization, radiation reduction, and clinical workflow enhancement. The INCISIVE project aims to address three major open challenges in order to explore the full potential of AI solutions in cancer imaging: (1) AI challenges unique to medical imaging, (2) Image labelling and annotation and (3) Data availability and sharing. In order to do that INCISIVE plans to develop and validate: (1) an AI-based toolbox that enhances the accuracy, specificity, sensitivity, interpretability and cost-effectiveness of existing cancer imaging methods, (2) an automated-ML based annotation mechanism to rapidly produce training data for machine learning research and (3) a pan-European repository federated repository of medical images, that will enable the secure donation and sharing of data in compliance with ethical, legal and privacy demands, increasing accessibility to datasets and enabling experimentation of AI-based solutions. The INCISIVE models and analytics will utilize various cancer imaging scans, biological data and EHRs, and will be trained with 1 PB of available data provided by 8 partners within the project. INCISIVE solution will be investigated in four validation studies for Breast, Prostate, Colorectal and Lung Cancer, taking place in 8 pilot sites, from 5 countries (Cyprus, Greece, Italy, Serbia and Spain), with participation of at least 2,600 patients and a total duration of 1.5 year. INCISIVE moves beyond the state of the art, by improving sensitivity and specificity of lower cost scanning methods, accurately predicting the tumor spread, evolution and relapse, enhancing interpretability of results and democratizing imaging data.

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