The particularity of paediatric cancers being rare diseases necessitates a collaborative approach to collate and integrate the data collected in all Member States, including best practices and new technologies in order to further develop common solutions. The use of big data for better insights in cancer genesis, outcomes and the long-term side effects of treatments is currently under-developed. Artificial intelligence and machine learning are powerful tools allowing for complex data analytics on large-scale data sets with great potential for fostering precision cancer medicine for all young people in Europe.
- The project will support the development of multi-national approaches to facilitate capturing data on paediatric cancer from multiple sources, and build a multi-stakeholder network to explore the applications of Artificial Intelligence technologies in paediatric cancer.
- The project will develop a state-of-the-art report to help understanding the challenges, needs and gaps in capturing data on paediatric cancer across the Union or the EEA countries, or both.
- The project will develop a framework to find solutions and prioritise opportunities to bridge existing gaps with a multi-national, multi-disciplinary approach.
- Mapping and building on existing multi-disciplinary and multi-national platforms/datasets and registries, the project will pave the road to a one-stop shop European point of access for integrated healthcare and research data platforms that collate clinical data, including, for example, clinical history, relevant diagnostic tests (pathology, genomics, radiological imaging), treatment interventions and clinical outcomes for childhood cancers.
- The project will create a multi-stakeholder network to connect and facilitate the exchanges and dissemination of best practices in clinically relevant Machine-Learning and Artificial Intelligence technologies between all relevant stakeholders, including paediatric oncology, technology developers, and the European Reference Network for Paediatric Oncology (ERN PaedCan), and experiment on their application in relation to multi-national large-scale data sets.
- The project should focus on multiple applications, for example radiological imaging, digital pathology, integrated genotyping and outcome prediction algorithms and clinical decision-making.
- The project will support research and further collaboration on Artificial intelligence technologies applied for diagnosis and treatment of paediatric cancers. Project results are expected to cover a representative range of stakeholders and solutions across Union or the EEA countries, or both.
- The project is expected to link to and collaborate with relevant Union initiatives (including the European Reference Network for Paediatric Oncology, ERN PaedCan) and build on Union-funded projects (for example, the Paediatric Rare Tumours Network – PARTNER project).
18 August 2020 17:00:00 Brussels time