Today’s rich digital information environment is characterized by the multitude of data sources providing information that has not yet reached its full potential in eHealth. CrowdHEALTH will introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants. HHRs will be transformed into Social HHRs communities capturing the clinical, social and human context of the population segmentation and as a result the collective knowledge for different factors depending on the communities formulation criteria (e.g. demographics, diseases, lifestyle choices, nutrition, etc). CrowdHEALTH will deliver a secure integrated ICT platform that seamlessly integrates big data technologies across the complete data path, providing of Data as a Service (DaaS) to the health ecosystem stakeholders. CrowdHEALTH will develop policy modeling techniques to facilitate the inclusion of Key Performance Indicators (KPIs) in policies and the correlation of these KPIs both with all health determinants captured in HHRs and with information from other domains towards a “health in all policies” approach. Creation and co-creation (cross-domain) of policies will be feasible through a rich toolkit, which will be provided on top of the DaaS, incorporating mechanisms for causal and risk analysis, as well as for compilation of predictions. Through the toolkit, multi-modal targeted policies addressing various time scales (long- / short- term), locations (area, regional, national, international), populations, and evolving risks will be realized. CrowdHEALTH will facilitate policies evaluation (on complete policy and per-KPI levels) and optimization through adaptive and incremental visualizations of simulations and outcomes of evidence based analysis of prevention strategies. CrowdHEALTH will collect data and will be validated through 5 pilots addressing different environments (care centers, social networks, public environments, living labs, diseases monitoring).

Ovarian cancer (OC) is the most lethal of female cancers, often termed a “silent killer”. DISARM’s overall approach to tackle the significant gaps in hereditary OC management lies in tackling both key elements of risk assessment and early detection. The project will investigate multifactorial risk assessment versus standard practices in 4 EU Member States (MS) (Lithuania, Portugal, Czech Republic, and Greece), and will upscale and validate a set of easy-to-use, highly accurate and affordable technologies in five countries (UK, Lithuania, Portugal, Czech Republic, and Greece). Several intelligent digital assets will optimally support and enhance our clinical studies, while a range of multifaceted activities will ensure the future uptake and adoption of DISARM solutions. The project aligns with the Innovation Action character of this topic by focusing on both mature technologies that can be upscaled in routine healthcare and on emerging technologies that have already shown a potential to justify larger scale validation activities. Our ultimate ambition is to holistically investigate the preconditions and set the stage for rolling out proven solutions in routine OC risk assessment, and in parallel to create further evidence for the introduction of novel promising elements in early detection programmes. DISARM gathers 26 partners from 12 countries (10 EU MS, the UK and Canada), thereby exhibiting a significant geographic coverage, strengthening European and international collaboration and ensuring widespread diffusion of the project results. This action is part of the Cancer Mission cluster of projects on ‘Prevention and Early Detection (early detection heritable cancers)

The latest cancer statistics highlight encouraging advances in decreasing cancer-related mortality. However, given that one in two people will be diagnosed with cancer in their lifetime, and due to the growing and ageing population, the absolute number of people living with cancer is set to keep increasing substantially in the near future. The main objective of ASCAPE is to take advantage of the recent ICT advances in Big Data, Artificial Intelligence and Machine Learning to support cancer patients’ quality of life and health status. To achieve its objective, ASCAPE will create an open AI infrastructure that will enable health stakeholders (hospitals, research institutions, companies, etc.) to deploy and execute its AI algorithms locally on their private data. Any new knowledge produced by this process will be sent back to the open AI infrastructure. This way the knowledge will be shared among everyone while the medical data will still remain private. The services to be designed, piloted and deployed inside this project will include intelligent interventions for physiological and psychological support, improved patient and family counselling and guidance, early diagnosis and forecasts of ill-health, identification of disease trajectories and relapse, improved health literacy etc. ASCAPE will focus the training of the AI in two types of cancer, breast and prostate. This way, it will achieve sufficient coverage across genders as well as age groups, hence facilitating its ongoing improvements and applicability towards any type of cancer in the future. The ASCAPE project will be developed in 36 months by a competitive consortium of 15 partners from 7 countries, which corresponds to a well-balanced structure, involving big companies, SMEs, research centres and universities. Despite the great diversity of entities within the proposal, ASCAPE partners bring state-of-the-art complementary skills ensuring the ability of the consortium to develop the proposed solutions.

The burden of cancer is rising globally and is estimated to have reached 18.1 million new cases and 9.6 million cancer deaths in 2018. Despite the rising cancer incidence, improvements in early detection and therapeutic treatment have improved cancer survival. As a consequence, the number of cancer survivors is increasing globally, creating the need to improve not only treatment but also wellness and follow‐up care. Cancer treatment often involves combined modalities such as surgery, chemotherapy, and radiotherapy. In the past decades, more effective and targeted therapeutic modalities and less destructive cancer treatments have been developed such as immunotherapy and drug‐targeted therapy. Even so, cancer and its treatment have important physical and psychosocial sequelae. ONCORELIEF is a 36-month action that will leverage the above 6 drivers in order to skillfully and methodologically overcome technical challenges, by introducing new approaches that will allow the utilization of big datasets in order to develop a user-centered AI System to facilitate the integration of QoL assessment instruments through the use of PROMs and PREMs in order to improve post-treatment health status, increase the wellbeing, and follow‐up care of cancer patients. This will be achieved through an intuitive smart digital assistant (Guardian Angel), able to provide personalized support in post-treatment activities and tasks, suggest actions regarding the patients' overall health-status, improved wellbeing and active health-care and ultimately maintain him/her engaged on a wellness journey that will safeguard his/her health over the foreseeable prolonged post-cancer treatment period. To achieve this, ONCORELIEF builds on the combined knowhow of its interdisciplinary industry-driven consortium that brings together state-of-the-art technological skills, design thinking methodology and occupational psychology/health sciences.