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 cancerSEE MORE
INCISIVE is a 42-months research project, funded under the call DT-TDS-05-2020 – AI for Health Images.
The INCISIVE project aims to develop and validate an AI-based toolbox that enhances the accuracy, specificity, sensitivity, interpretability and cost-effectiveness of existing cancer imaging methods.
Additionally, INCISIVE’s work will be enriched by an automated Machine Learning (ML)-based annotation mechanism and through the development of an interoperable pan-European 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, towards the large-scale adoption of such solutions in cancer diagnosis, prediction and follow-up.
In its lifetime, INCISIVE will make use of multimodal data sources, including imaging, biological and Electronic Health Record (HER).
An AI-based toolbox consisting of novel AI models, combined with a set of predictive, descriptive and prescriptive analytics, enabling the multi-modal exploration of the available data sourc...
An Interoperable pan-European federated repository of health images that allows sharing data in compliance with legal, ethical, privacy and security requirements, for AI-related training and...
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