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VISION: Cardiovascular disease is the main cause of mortality worldwide, representing about a third of annual deaths, and patients’ medical care produces a large amount of data. DataTools4Heart will design methods to reuse such data to facilitate research and improve the conditions of cardiovascular patients. The DataTools4Heart toolbox will be designed, tested, and implemented in several countries while ensuring the compliance of all legal (e.g., privacy) constraints in the cardiology domain.

MISSION: DataTools4Heart aims to improve the lifestyle of patients suffering from cardiovascular diseases by developing a comprehensive, federated, privacy-preserving toolbox for data reuse in cardiology. The tools include a platform that will securely access data from different hospitals and transform them into their digital counterparts (synthetic data) to be used by researchers and clinicians across the world. The access into large-scale multi-source cardiology data will be facilitated by the creation of virtual assistants.

FOCUS: Through the capacity of all its participants and the consortium, DataTools4Heart will focus on unlocking currently inaccessible cardiovascular health data. DataTools4Heart operates in response to the European Society of Cardiology (ESC) call for a major shift towards integrative data-driven approaches to develop personalised cardiovascular medicine. Multi-site federated health data use will be allowed, thanks to the contributions from clinical centres from seven EEA countries, namely Spain, the Netherlands, United Kingdom, Italy, Sweden, Romania, and Czech Republic. They will constitute a representative sample of the European healthcare landscape, to contribute to the creation of the European Health Data Space. OBJECTIVES: DataTools4Heart will create a comprehensive cardiology data toolbox for clinicians, researchers, and data scientists. Tools will allow data ingestion and harmonisation, Natural Language Processing in multiple languages, federated machine learning and data synthesis. Virtual assistants will aid users in navigating large multi-source cardiology data while adhering to European regulations and data standards

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101057849

Principal Investigator: Dott. Alfredo Cesario

Budget: € 260.250 Duration: October 2022 – September 2026

Website: https://www.datatools4heart.eu

COVID-X aims to provide competitive and market oriented European SMEs access to knowledge,
technology, capital and markets with the aim to place new products/ services in the market with the
goals of fighting the COVID-19 pandemic.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016065

Principal Investigator: Dott. Luca Tagliaferri

Budget: € 50.000 Duration: April 2021 – January 2022

Website: https://www.covid-x.eu/

The specific focus of iHELP is on early identification and mitigation of the risks associated with Pancreatic Cancer based on the application of advance AI-based learning and decision support techniques on the historic (primary) data of Cancer patients gathered from established data banks and cohorts. This analysis helps to (i) determine key risks associated with Pancreatic Cancer, (ii) develop predictive models for identified risks, and (iii) develop adaptive models for targeted prevention and intervention measures. Based on these developments, the project selects high-risk individuals that are invited to take part in the pilot activities or digital trials. The digital trials are carried out through user-centric mobile and wearable applications that apply proven usability principles to offer more awareness, more engaging experience for health monitoring, risk assessment and personalised decision support. Close collaboration between clinical and AI experts focus on drawing decision support against identified/predicted risks and providing personalised recommendations (e.g. lifestyle changes, behavioural nudges, screening test etc) to the participants in the digital trials. The iHELP (mobile and wearable) technology solutions help in validating iHELP solutions and raising health related awareness at individual level. The (secondary) data gathered through the mobile and wearable applications (concerning life style, behavioural, social interactions and response to targeted prevention and intervention measures) is integrated with primary data in the standardised HHR format – within a big data platform. Frugal AI-based learning techniques are developed to provide near real-time risk assessment based on the integrated and standardised HHR data. iHELP solutions are targeted at multiple stakeholders, including policymakers that will get decision support on the design of new screening programs and new guidelines for bringing improvements in clinical and lifestyle aspects.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017441

Budget: € 482.222,50 Duration: 01/01/2021 – 31/12/2023

Website: www.ihelp-project.eu

Real-world data and AI to enable tailored-made care for patients with COPD and comorbid complex chronic conditions (CCCs)

Over the course of four years (2021-2025), RE-SAMPLE will work to transform the healthcare journey of patients with Chronic Obstructive Pulmonary Disease (COPD) and comorbidities, and to set a standard of care for patients suffering from complex chronic conditions.

Using Artificial Intelligence (AI), RE-SAMPLE hopes to gain unique insights into the complex relationships between patients’ clinical and non-clinical characteristics, and how these impact disease progression, mental wellbeing, and physical health. The data and analyses will also serve as a basis for predictive models that will help patients and their doctors make treatment and lifestyle changes in time to reduce serious complications. One of the project’s hallmarks is the early integration of security and privacy settings across all technical (the system itself will be designed from this perspective) and non-technical (the project will adhere to rigorous ethical and data protection standards) aspects of RE-SAMPLE.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 965315

Principal Investigator: Prof. Luca Richeldi

Budget: € 690.625 Duration: March 2021 – February 2025

Website: www.re-sample.eu

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The vision of TERMINET is to provide a novel next generation reference architecture based on cutting-edge technologies such as SDN, multiple-access edge computing, and virtualisation for next generation IoT, while introducing new, intelligent IoT devices for low-latency, market-oriented use cases.

TERMINET’s primary intention is to bring (more efficient and accurate) decisions to the point of interest to better serve the final user targeting at applying distributed AI at the edge by using accelerated hardware and sophisticated software to support local AI model training using federated learning. Our solution aspires to reduce the complexity of the connecting vast number of heterogeneous devices through a flexible SDN-enabled middleware layer. It also aims to design, develop, and integrate novel, intelligent IoT devices such as smart glasses, haptic devices, energy harvesting modules, smart animal monitoring collars, AR/VR environments, and autonomous drones, to support new market-oriented use cases. Great expectation of the proposal is to foster AR/VR contextual computing by demonstrating applicable results in realistic use cases by using cutting-edge IoT-enabled AR/VR applications. By designing and implementing an IoT-driven decentralised and distributed blockchain framework within manufacturing, TERMINET aims to support maintenance and supply chain optimisation. Our solution intends to apply a vertical security by design methodology by meeting the privacy-preserving and trust requirements of the NG-IoT architecture. To foster standardisation activities for the IoT ecosystem, TERMINET will provide novel disruptive business models. For the evaluation of its wide applicability, TERMINET will validate and demonstrate six proof-of-concept, realistic use cases in compelling IoT domains such as the energy, smart buildings, smart farming, healthcare, and manufacturing.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 957406

Principal Investigator: Prof. Vincenzo Valentini

Budget: € 103.125 Duration: November 2020 – October 2023

Website: https://terminet-h2020.eu