stroke cases yearly worldwide
leading cause of death in Europe and Finland
direct costs for society
Transient ischemic attack (TIA) is a precondition of a stroke attack, which is often called a mini-stroke. Although 10.5% to 18.2% of patients with TIA will have a stroke within 90 days, more than 31-61% of the TIA patients are currently misdiagnosed.
There is an urgent need for an early and correct diagnosis of patients who experience a TIA and/or Stroke. The key to addressing this need is in combining medical information in new ways and extracting actionable recommendations from it. This is a field where modern Artificial Intelligence (AI) approaches can help. However, today there is a lack of data-driven AI-powered decision support systems for stroke prevention and diagnostics.
Addressing The Need
Stroke-DATA will capitalize on the recent advancements in AI, and together with the richness of data, provide decision management support tools for stroke and TIA diagnosis and prevention. Such approaches would facilitate differential diagnostics, triaging, and management of cerebrovascular conditions in a cost-effective way.
The Stroke-DATA project will create a prototype of the next-generation continuous risk calculator and decision support system. If the data amount and quality allows, the novel advanced methods of stroke diagnostics will lead to:
- More rapid and accurate diagnosis and early preventive treatment, “the 90-day stroke risk” can be decreased by 80% after the TIA episode
- Decreased number of deaths in the misdiagnosed TIA cases
- Decreased hospitalization rate of stroke patients due to the earlier thrombolytic therapy in long-distance situations
- Increased competitiveness of Finnish medical technology companies in the neurology market.
1. Co-create mobile solution that improves stroke care and cerebrovascular disorders risk diagnostics for risk patients
2. Co-create and apply advanced AI machine learning algorithms for stroke prevention
3. Pilot the data-driven support system in the pre-hospital context to test its feasibility.
1. Co-create advanced AI and machine learning algorithms for stroke diagnostics
2. Co-create advanced decision support system for stroke / TIA diagnostics
3. Validate the potential of microwave imagining and NIRS brain fluid sensors combined with other data in the accuracy of stroke diagnosis
4. Validate the feasibility of combining heterogeneous data with AI and machine learning approaches in for stroke diagnosis.
1. Develop a system dynamic model for predictive impact evaluation in the case of improved diagnostics of stroke cases
2. Develop internationalization model for the Stroke-Data solutions (e.g. in Nordics, Europe, Singapore, Australia).
Targeted Digital Health Market Sectors
The development of stroke prevention and diagnostics solutions requires ecosystemic co-creation and new types of development practices between researchers, companies, and hospitals from different countries. In particular, it cannot be done without multidisciplinary expertise from technology, business, and medical fields. This all is possible only in our Stroke-DATA consortium that involves the advanced companies from Finland, National neuro centres from Finland and neurologists from Oulu (OUH) and Kuopio University Hospitals (KUH) /the University of Eastern in Finland (UEF).
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