RES-Q+ will build on the success of RES-Q (REgistry of Stroke Care Quality) - currently, used by many EU countries and 74 worldwide - to improve stroke care quality by collecting and analyzing hospital discharge reports. RES-Q+ will revolutionize these improvements by capturing the whole patient pathway. The solution will combine NLP with a clinically-validated semantic model to automate ingestion of hospital discharge reports in different languages and assist with audit and feedback. This will include creating a standard model for such reports and using AI to impute missing data. Further augmentations include the creation of two novel AI voice assistants, one to help patients provide feedback on their health and the other to help physicians provide high quality care. We will integrate all these tools into RES-Q+. This will be the basis for a European Open Stroke Data Platform, an open research platform for data aggregation, semantic harmonization and interoperability across European countries to promote the use and re-use of health data. We will facilitate efforts to define a standard European Stroke Hospital Discharge Report Exchange Format as a tool for better secondary use of data and healthcare in general. Consortium legal partners will develop a comprehensive legal and ethical toolbox as guidance towards legal compliance. This will boost wider adoption of such novel AI-based solutions by integrating all current and proposed Union legislation. Our clinical partners will provide medical records and steer the development to maximize clinical utility and validate final solutions. RES-Q+ will be deployed globally to solidify our position as European and global leader in quality improvement. Eventually we will guarantee citizens a similar level of quality control during hospitalizations as when flying in a commercial plane.

The main contribution of PROCareLife consists in proposing an integrated scalable and interactive care ecosystem, which can be easily adapted to the reality of several chronic diseases, care institutions and end-user requirements, benefiting all the involved actors, from patients, to caregivers and health professionals. Its main contributions consist of: (a) building an integrated scalable and interactive care ecosystem for neurodegenerative diseases and adaptable to other chronic conditions; (b) finding the best actions/measures from a medical and social point of view that can facilitate an improved quality of life, awareness and care management for senior users suffering of neurodegenerative and/or other chronic diseases; (c) provide a personalized recommendation and interaction model, which can support the user through gamification techniques to adopt healthy habits, maintain a good daily routine and follow the prescribed actions by the professionals for maintaining and improving their health condition; (d) enable multi-disciplinary communication between all involved stakeholders, better time management for social and health professionals and contribute to achieving a cost-efficient, flexible and high adaptable solution for senior users suffering of short or long term conditions.

Direct costs of brain disorders make up for 60% of the total costs – which EBC estimated at 800 bln€/year in Europe. At European level, this health budget far exceeds that of cardiovascular diseases, brain diseases and diabetes together. ALAMEDA will research, develop and exploit the next generation of personalized AI healthcare support systems that improve the rehabilitation treatment of Parkinson’s, Multiple Sclerosis, and Stroke (PMSS) patients. Stemming from very specific clinical use cases, ALAMEDA will develop user-friendly solutions that will be designed and evaluated on the principles of value-based health. The consortium brings together established medical research teams, AI researchers, medical software vendors and healthcare market experts to demonstrate AI-based personalised prediction, prevention, and intervention approach in three (3) real world pilots. Liaisons have been established with projects MULTI-ACT and IDEA-FAST and the carefully structured workplan, embodies an integrated and harmonized approach with active patients’ engagement towards meeting the ALAMEDA objectives and delivering market-relevant outcomes of significant exploitation potential.

Parkinson's disease (PD) presents a complex challenge due to its progressive neurodegenerative nature, affecting various body systems. Despite decades of research, understanding its onset and progression remains unclear, complicating early diagnosis and treatment. Recent advancements in PD physiopathology suggest promising treatments to slow disease progression, yet reversing cellular degeneration remains elusive. With novel therapies emerging, the need for early detection tools is urgent. However, validated biomarkers for PD diagnosis are lacking, relying on subjective scales like Hoehn and Yahr or costly medical imaging techniques. The accumulation of misfolded -Synuclein (-Syn) proteins in PD pathology has sparked interest, but defining diagnostic roles requires further investigation. Recent findings of -Syn in neuronal-derived extracellular vesicles (NDEVs) from PD patients suggest a potential for novel diagnostic methods. Our proposed project, VMPiRE, aims to conduct a longitudinal study involving 600 PD patients and 600 healthy subjects to explore -Syn isoforms and related biomarkers in NDEVs for early PD detection. We plan to develop and validate an innovative in-vitro diagnostic (IVD) test capable of detecting PD's earliest stages and estimating disease prognosis and progression. Utilizing AI models to generate data analysis algorithms and collaboration with leading analytical laboratories and IVD manufacturers, we aim to ensure the reliability and feasibility of the developed prototype. Through consortium efforts, we envision licensing the generated intellectual property to drive the commercialization of our results. This can improve early screening of 270,000 new cases of PD could be detected early and improve the disease management of 9.4 M people currently diagnosed of PD and avoid losing a total of 5.8 million disability adjusted life years (DALYs) by 2028 leading also the development of better treatments.