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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

Descripción del proyecto

Mejora del diagnóstico y la predicción del cáncer con la inteligencia artificial

A pesar de que la inteligencia artificial (IA) y el aprendizaje automático (AA) ofrecen oportunidades sin precedentes para mejorar la detección del cáncer, distintas dificultades técnicas y la falta de disponibilidad de datos obstaculizan su uso. El proyecto financiado con fondos europeos INCISIVE tiene como objetivo desarrollar un conjunto de herramientas para mejorar la precisión, especificidad y sensibilidad de los métodos existentes de imagenología del cáncer. La idea es generar un repositorio paneuropeo de imágenes médicas que pueda utilizarse para la formación basada en el AA para distintos tipos de cáncer. Los resultados del proyecto ayudarán a predecir con precisión la propagación, evolución y recidiva de tumores, además de ayudar a estratificar pacientes.

Objetivo

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.

Convocatoria de propuestas

H2020-SC1-FA-DTS-2018-2020

Consulte otros proyectos de esta convocatoria

Convocatoria de subcontratación

H2020-SC1-FA-DTS-2019-1

Régimen de financiación

RIA - Research and Innovation action

Coordinador

MAGGIOLI SPA
Aportación neta de la UEn
€ 702 500,00
Dirección
VIA DEL CARPINO 8
47822 Santarcangelo Di Romagna
Italia

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Región
Nord-Est Emilia-Romagna Rimini
Tipo de actividad
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Enlaces
Coste total
€ 702 500,00

Participantes (28)