THE DATA-DRIVEN INNOVATION IS HERE … › media › siope › ...Health discoveries, risk prediction, early detection of diseases Empower health professionals and citizens Delivering

Health discoveries, risk prediction, early detection of diseases Empower health professionals and citizens Delivering better health and care

THE DATA-DRIVEN INNOVATION IS HERE

Digital Health

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EHR

GENOMICS

PHYSIOLOGICAL AND MOLECULAR MEASUREMENTS

Digital Transformation of Health and Care Challenges and opportunities

Access, integration, communication of health data

Cross linking datasets Interoperability data/systems/technologies Cybersecurity and Data Protection

Innovative solutions for prevention, diagnosis, treatment, care

Artificial Intelligence, clinical decision support systems

HPC, Blockchain, Big data analytics, IoT, cloud computing

Visualisation, NLP

Efficiency of health and care systems, better outcomes, personalised medicine, integrated care, well-being, citizens empowerment, …

Privacy, data deluge, fragmentation, uptake, inequalities, …

Communication Artificial Intelligence for Europe COM(2018) 137 final

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CNECT H3 activities related to Cancer

• Support the development and uptake of AI solutions to fight cancer

• Gathering and exploitation of health data initiatives, such as the

1+M genomes initiative for linking genomic databases, for prognosis,

better diagnosis and follow-up of cancer treatments (with a specific

Cancer Working Group)

• Personalized Cancer Medicine project’s portfolio

• Creation of a common health data space, with a medical images

database (linked to interoperability, EHR XF and registries)

• Research and innovation actions related to Cancer

Examples of H2020 Cancer-related projects

• BD2Decide uses AI and big data to support clinicians treating head and neck cancer

• IASIS integrates heterogeneous big data sourcesto support clinicians developing more personaliseddiagnoses and treatments for lung cancer

• PRIMAGE offers predictive tools to assist diagnosis, prognosis, therapies choice and treatment follow up for pediatric cancer, based on the use of novel imaging

• IPC: combines knowledge-base,machine-learning and mechanistic models to predict optimal standard and experimental therapies for personalized pediatric cancer

• GAPs: SC1-DTH-01-2019: Big data and Artificial Intelligence for monitoring health status and quality of life after the cancer treatment, 35 M EUR, RIA

• Significant current CNECT H3 cancer-related projects’ portfolio

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