The Decision Support for Health (DSH) Group conducts research on ICT solutions, focusing on data analytics methods, that combine information from different modalities, such as sensors, electronic health records, unstructured data and other information sources. Our technical research areas include health monitoring technologies, data analysis (signal processing, AI and ML) and decision support system development. Current application areas include for example decision support for critical care and chronic diseases such as cardiovascular diseases, diabetes, and Parkinson’s disease. We also do research and development in health ICT standards and medical device regulations. All our research is done in close collaboration with health care professionals and companies. Our teaching focuses on health ICT (especially data analysis, and data-driven decision support, including AI and ML) and regulatory aspects of it.
Ongoing activities
Our group co-ordinates the ERA PerMed project PerCard (2022-2025). PerCard combines different data with novel analysis methods (AI, machine learning, signal processing) to deliver an improved risk modelling tool for cardiovascular diseases. The developed methods are explainable, practical, accessible, and affordable. Development combines existing Finnish and Italian data and new-to-be-collected data in Italy. Ethical and societal aspects, including gender and accessibility to all, receive especial attention.
In the HEU project SMASH-HCM (2024-2027), co-ordinated by TAU, we develop data-driven methods, linked to mechanistic modelling approaches to provide decision support in the case of Hypertrophic Cardiomyopathy (HCM). Our project aims to develop a cutting-edge digital-twin platform, integrating dynamic biophysical models and data-driven insights for personalized HCM stratification and improved disease management. Our group has the responsibility for the development of the decision support software solution, and develops methods that combine different modalities of information in an explainable manner.
In the Horizon Europe project COVend (2021-2025) we develop AI-based data analysis methods for improved management of Acute Resporatory distress Syndrome (ARDS) patients in critical care settings.
In the Horizon Europe Project CVDLink (2024-2027) we help developing high-impact, open access tools for cardiovascular disease decision support. We – Securely integrate medical, clinical, genetic, and other real-world data sources into a unified dataset – Create data and AI-driven tools to aid in the treatment, diagnosis, and prevention of cardiovascular diseases – Develop a Platform as a Service for healthcare providers and researchers, validated by studies in 5 countries.
In the Finnish project DTHOSVE (2023-2024), we create the prerequisites for launching an expertise network and its long-term resourcing in the area of digital health and wellbeing technology in Finland. We aim to expedit the sharing of good practices and experiences, the creation of internationally funded cooperation projects and the growth of cross-border RDI investments.
Explainable and Trustworty AI research (2022 – ) – The Trustworthy AI for Healthcare Laboratory at Tampere University is composed of a group of researchers that pursue to leverage the importance of Trustworthy AI in academic and civil society to enhance the AI solutions aimed at healthcare and improve their uptake by the different healthcare stakeholders. The Lab is affiliated with the Z-inspection ® initiative.
Furthermore, we have many ongoing activities with clinical partners in various areas of joint interest, e.g., Seinäjoki Hospital and South-Ostrobothnia Wellbeing County (data acquisition systems for critical care, assessing adequacy of anesthesia, resource planning for emergency care); Tampere University Hospital (critical care monitoring, holistic patient state prediction, smart alarms, decision support in management of cancer patients), Helsinki University Central Hospital (anesthesia monitoring in children).
Examples of earlier activities
Our H2020 project “ENVISION” (2020-2023) focuses on machine learning-based decision support for real-time surveillance of Covid-19 patients.
DiHECO (2020-2023) was a H2020 Twinning project to aiming to build the capacities for Kaunas University of Technology (KTU) to conduct high-quality research in the field of digital healthcare management and in particular digital healthcare services’ multi-sided platforms.
We have been working with Finnish companies Firstbeat and Aava (2021-2024) to study the effects of a personal technology driven workplace wellbeing intervention programme on wellbeing, productivity (presenteeism) and absenteeism in an intervention study. In here, we combined and analysed a large range of different data source to help develop personalized and adaptive interventions for occupational health.
In the EU H2020 project “DigiNewB” (2018-2020) where we developed conducting machine learning base solutions for the sepsis prediction of prematurely born babies in intensive care.
In the Käveli project (2018-2019) we built a system to monitor and analyze the walking patterns of Parkinson’s disease patients at home. Home monitoring was done using the sensors of the smartphone, force sensor integrated to smart insoles of shoes and wrist-worn accelerations sensors. The target of the project was to study if the home measurements could be utilized for assessing the state of the disease and for following its changes and the effect of medication.
In the Digital Health Revolution project we have researched the human-centric personal health data management, data privacy and re-use. We have been developing and implementing a new architecture for health data management utilizing the MyData principles. Linked to the project, also a TUT spin-off company focusing on wellness data integration was created.
We have conducted research on wearable sensors, with special focus on improving the accuracy of wearable optical heart rate measurement systems.
We have also researched the area of technology-assisted health coaching and developed in TEKES/Business Finland and EU projects a web-based tool health and wellness coaching targeted for preventive health care. The results of the project have been commercialized through the PHI team spin-off company Movendos Oy.