Elli Valla

This multidisciplinary study aims to decrease cardiovascular mortality in Estonia by increasing treatment adherence and empowering patients to create a supportive self-management environment for monitoring their health and actively participating in the treatment process. Analysing 1) the LDL-cholesterol values of North Estonia Medical Centre (NEMC) patients to find underdiagnosed and undertreated patients and 2) treatment adherence to lipid-lowering drugs (LLD). Identifying patient groups who need additional support. During the pilot project, a novel application will be developed, together with personal support, used to increase LLD adherence. The novelty of the tool – combining the data used in Estonia from the Nationwide Health Information System, ePrescription, and NEMC electronic medical record with the data collected by the patient and enabling two-way communication between the patient and medical staff. In the last stage of the study, an impact assessment of the tool is planned.

The present project aims to develop novel and enhance existing methods of explainable artificial intelligence for the analysis of human motor functions. Pilot studies have demonstrated promising results to support the diagnosis of neurodegenerative diseases. In addition, we plan to extend the area of application from medicine to cognitive development and cognitive fatigue analysis. The integration of the explainer component will provide medical professionals with the necessary transparency of the decisions made by AI. Application in the area of cognitive development to support the school education process. Cognitive fatigue is known to cause severe injuries and serious financial losses. In-depth understanding of this phenomenon and ability to recognise mental fatigue targets to make the work environment safer and reduce monetary and non-monetary losses in the process of work.

The overall goal of the project is to increase the number of healthy life years of the population. Currently, Estonia has recorded one of the lowest number of healthy life years at birth in the EU. To achieve this goal, three closely related areas of digital health are researched, developed and piloted. We use the standardized data exchange environment and digital data of the Estonian health information system (EHIS) to develop applications that increase the use of data collected by the person for health promotion, prevention and control of chronic conditions. Second, we focus on sensors and digital applications supported by artificial intelligence (AI) to allow a person to collect both biosignals and textual data in machine-readable form. With this, we speed up the detection of health risks and reduce the healthcare workload. Thirdly, we develop various AI methods by combining the data in EHIS and the Health Insurance Fund's database, as well as the data collected by the person.