Project description
Improving cancer diagnosis and prediction with artificial intelligence
Although artificial intelligence (AI) and machine learning (ML) provide unprecedented opportunities for improved cancer detection, various technical challenges as well as a lack of data availability hamper their utilisation. The EU-funded INCISIVE project aims to develop a toolbox for enhancing the accuracy, specificity and sensitivity of existing cancer imaging methods. The idea is to generate a pan-European repository of medical images that can be used for ML-based training for various types of cancer. The project's deliverables will assist the accurate prediction of tumour spread, evolution and relapse, in addition to helping stratify patients.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
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Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
47822 Santarcangelo Di Romagna
Italy
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Participants (27)
106 82 ATHINA
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57001 Thermi Thessaloniki
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82100 Benevento
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08034 Barcelona
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1466 Luxembourg
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
15125 Marousi Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
N7 7PX LONDON
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1000 Bruxelles / Brussel
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
546 36 THESSALONIKI
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21000 Novi Sad
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11080 Beograd-Zemun
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80138 Napoli
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08005 Barcelona
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115 21 ATHINA
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1687 Nicosia
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00133 Roma
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10561 Athina
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00014 HELSINGIN YLIOPISTO
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08036 Barcelona
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
08036 Barcelona
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50132 Limassol
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
KT1 2EE KINGSTON UPON THAMES
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3036 Lemesos
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1000 Bruxelles / Brussel
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1060 Sint-Gillis
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
28050 Madrid
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145 65 AGIOS STEFANOS
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.