Develop and evaluate a set of novel data analytics and predictive modelling solutions. These analysis tools will be designed to work with data in the European Stroke Hospital discharge reports Exchange Format (EUSHDR).

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These tools will be data driven and implemented using statistical and machine learning methods. These models will be integrated into the RES-Q+ virtual assistants and will provide extra functionality for responding to end-user queries and enable novel forms of engagement (such as motivational support and target setting to support compliance with rehabilitation programmes). Furthermore, analysis of these tools through xAI has the potential to reveal new insights into risk and resilience factors not previously possible at a European population level.