Suchergebnisse

Hypertrophic cardiomyopathy (HCM) is the most common inherited genetic heart disease, and its most feared outcome is a sudden death even in a young otherwise healthy adult. The EU-funded project SMASH-HCM aims at dramatically improving HCM stratification and disease management, both for clinicians and patients. The project combines data from the patients at multiple levels, from genetic and molecular data to in-silico physiological and family history data and creates in-vitro and computational models of the disease at these various levels. A digital twin of the patient will be formed based on these data modelling tasks. Modelling approaches, data-driven artificial intelligence and knowledge existing in literature will complement each other to provide decision support for the clinicians to optimize interventions, and actionable information about the disease status and development will be offered to the patient.

The COVend project aims at delivering a new effective therapy, FX06, against the SARS-CoV-2 virus infection for the management of the COVID-19 disease in hospitals. Nine of the 17 partners of the project consortium are hospitals responsible for collecting study subjects and administering the FX06 therapy to the patients. Although the clinical trial (IXION) has the main role in the project, the project has also a work package which develops and applies artificial intelligence (AI) methods to the data collected during the 28-day study period from the patients receiving the therapy. The AI work package applies exploratory data analysis methods to find patterns and profiles of the patients. Combined with the data about treatment methods and patient outcomes, the aim is to provide decision support for the therapy intervention in the later stage of the project.

The DiHECO project aims at studying the role and potential of digital healthcare platforms in the European, mostly publicly arranged, healthcare service ecosystem. The project, divided into a few subprojects, tries to identify areas of research that can grow into impactful larger European projects with industry co-operation. DiHECO aims also at further developing the capacity of participants, particularly the Kaunas University of Technology, to perform relevant research in this area. In its first year, the project has made progress according to plan through joint research activities and networking events. These include the digital health tracks of the researcher and industry forum of the ICTE 2021 conference and two grant writing workshops and a scientific writing workshop.

The Envision project aims at developing artificial intelligence-based tools for supporting the treatment of critically ill COVID-19 patients in the intensive care unit. Twelve European hospitals participate in the collection of patient data for the development and validation of the artificial intelligence tools. Ten potential use cases have been identified as development targets. Data analysis and results from expert interviews are applied to define the clinically most relevant parameters and functional use cases to be used in providing decision support for the clinicians in the intensive care units for this patient group. The resulting artificial intelligence-based tool may be beneficial in the management of the next similar epidemics, as well.