In Europe, prostate cancer (PCa) is the second most frequent type of cancer in men and the third most lethal. Current clinical practices, often leading to overdiagnosis and overtreatment of indolent tumors, suffer from lack of precision calling for advanced AI models to go beyond SoA by deciphering non-intuitive, high-level medical image patterns and increase performance in discriminating indolent from aggressive disease, early predicting recurrence and detecting metastases or predicting effectiveness of therapies. To date efforts are fragmented, based on single–institution, size-limited and vendor-specific datasets while available PCa public datasets (e.g. US TCIA) are only few hundred cases making model generalizability impossible. The ProCAncer-I project brings together 20 partners, including PCa centers of reference, world leaders in AI and innovative SMEs, with recognized expertise in their respective domains, with the objective to design, develop and sustain a cloud based, secure European Image Infrastructure with tools and services for data handling. The platform hosts the largest collection of PCa multi-parametric (mp)MRI, anonymized image data worldwide (>17,000 cases), based on data donorship, in line with EU legislation (GDPR). Robust AI models are developed, based on novel ensemble learning methodologies, leading to vendor-specific and -neutral AI models for addressing 8 PCa clinical scenarios. To accelerate clinical translation of PCa AI models, we focus on improving the trust of the solutions with respect to fairness, safety, explainability and reproducibility. Metrics to monitor model performance and a causal explainability functionality are developed to further increase clinical trust and inform on possible failures and errors. A roadmap for AI models certification is defined, interacting with regulatory authorities, thus contributing to a European regulatory roadmap for validating the effectiveness of AI-based models for clinical decision making.

The COVID-19 pandemic has highlighted the importance of the continuity of vital services, has shown the need to work together for the common good. It has proven that a pandemic is not only a health crisis and that it does not only disrupt Critical Infrastructures (CIs), but that there is an extremely important link between the resilience of CIs and our societies. The economic crisis caused by the pandemic also provides a unique opportunity to jointly ‘build back better’ with the focus on sustainability and green recovery. SUNRISE will facilitate active collaboration of CIs across Europe to share best practices and jointly tackle future pandemics. By Q3/2025, this collaboration will result in a new stable working group for resilience to pandemics with at least 100 members. With a group of 4 CI authorities, 16 CI operators, 3 other CI stakeholders, 4 experts in Social Sciences and Humanities, 2 experts in epidemiology and climate extremes, and 12 security researchers and SW developers, we will: (1) Identify pandemic-specific vital services and CIs, their dependencies, risks, cascading effects, and effective measures to tackle them at European level. (2) Develop a comprehensive strategy (TRL8) and four innovative tools (TRL7) ensuring greater availability, reliability, security, robustness, trustworthiness, cost-effectiveness, climate-friendliness, and continuity of pandemic-specific vital services in Europe: Tools for risk-based access control, resource demand prediction and management, cyber-physical resilience, and remote infrastructure inspection. (3) Pilot the results in operational environments of the CIs while tackling some of their biggest pain points exposed by the current pandemic. (4) Promote our approach across Europe to ensure a united front and resilience of CIs to pandemics. We will carefully consider legal, ethical, societal, economic, and climate aspects, ensuring that our results address not only the needs of the CIs, but also those of our society.

It is a fact that the European population growth is slowing down, while the population ageing accelerates. Rapid increases in the elderly population are predicted for the coming decades due to the ageing of post-war baby births. Within Europe’s ageing population, Hearing Loss, Cardio Vascular Diseases, Cognitive Impairments, Mental Health Issues and Balance Disorders, as well as Frailty, are prevalent conditions, with tremendous social and financial impact. Preventing, slowing the development of or dealing effectively with effects of the above impairments can have a significant impact on the quality of life and lead to significant savings in the cost of healthcare services. Digital tools hold the promise for many health benefits that can enhance the independent living and well-being of the elderly. Motivated by the above, the aim of the SMART BEAR platform is to integrate heterogeneous sensors, assistive medical and mobile devices to enable the continuous data collection from the everyday life of the elderly, which will be analysed to obtain the evidence needed in order to offer personalised interventions promoting their healthy and independent living. The platform will also be connected to hospital and other health care service systems to obtain data of the end users (e.g., medical history) that will need to be considered in making decisions for interventions. SMART BEAR will leverage big data analytics and learning capabilities, allowing for large scale analysis of the above mentioned collected data, to generate the evidence required for making decisions about personalised interventions. Privacy-preserving and secure by design data handling capabilities, covering data at rest, in processing, and in transit, will cover comprehensively all the components and connections utilized by the SMART BEAR platform. The SMART BEAR solution will be validated through five large-scale pilots involving 5.000 elderly living at home in Greece, Italy, France, Spain, and Romania.

This ESFRI Preparation Phase Project will place the EBRAINS research infrastructure (RI) developed by the Human Brain Project (HBP) on a sustainable footing. The new organisational framework will allow EBRAINS to evolve from the largely EC-funded, HBP-developed RI into a sustainable “Hub-and-Node” RI on the ESFRI Roadmap. The Operation Phase EBRAINS RI will serve the whole brain research community, rather than the needs of a subset of users within that community; this will be reflected in a broader offering of tools and services by the RI. The Operation Phase RI will focus more on the processing, managing and sharing of data of all sorts, even those generated outside the RI, but will retain an important role in providing cutting-edge data-generating tools and services. While staying true to its roots in supporting basic research, it will expand its activities to support clinical research and innovative exploitation of brain-related technologies. The evolving RI offering will be determined with the help of a new governance structure, which focuses on determining the priority needs of the broad brain research community. The Operation Phase EBRAINS will be funded primarily by long-term commitments by the EU Member States and Associated Countries that are home to a Node in the EBRAINS RI. Objective 1: To put in place a financial, legal and governance framework for EBRAINS and prepare a plan to ensure the sustainable offering of the Service Capability by the Central Hub and the Nodes. Objective 2: To obtain the legally binding commitment of EBRAINS Consortium Partners to offer services needed by the brain research community by setting up EBRAINS Nodes. Objective 3: To deliver a complete overall technical design and associated cost estimate for the Service Capability. Objective 4: To decide the legal structure that EBRAINS will adopt for the Operation Phase and produce draft statutes for EBRAINS in that structure.

Sudden cardiac death (SCD) is a major public health problem accounting for ~20% of all deaths in Europe with an estimated yearly incidence of ~350-700,000, often in patients with previous myocardial infarction (MI). In SCD, the heart suddenly and unexpectedly stops beating. If untreated, the patient dies within minutes, but SCD can be successfully prevented by an implantable cardioverter-defibrillator (ICD). The ICD is highly effective, but is associated with potentially severe complications and high healthcare costs. Based on historical evidence, guidelines recommend prophylactic ICD implantation in post-MI patients with left ventricular ejection fraction (LVEF)≤35% to prevent SCD. However, only a minority of these patients will ever need the device. In addition, in absolute numbers the majority of SCD cases occurs in patients with LVEF>35% who are currently not considered for prophylactic ICD. Due to the inherent risks and considerable health care expenditures, a personalised treatment approach for ICD implantation is urgently required. Using state-of-the-art methods and large clinical datasets from established international cohorts and registries across different European geographies, PROFID will develop a clinical decision support tool (risk score) to predict the individual SCD risk and identify those post-MI patients that will optimally benefit from an ICD. Two parallel randomised clinical trials will validate implementation of the risk score to determine ICD implantation, while health economic analyses will assess its economic impact on health care systems. A software tool for clinical use of the risk score will be implemented, and a pilot run in 3 European regions with participation of insurance companies and authorities. The unique composition of the consortium with key opinion leaders, patient organisations, large hospital chains, payers, policy makers and state authorities across Europe, will ensure implementation into routine clinical practice.