1. Patient trajectories and XAI
A key prerequisite for precision healthcare is patient and disease characterisation, where patient trajectories can play an important role. Patient trajectories are a means of illustrating the temporal disease progression and correlations. These models often suffer from inscrutability, which prevents pervasiveness of AI applications in healthcare. Therefore, in subject area 1, we will address the patient trajectory and Explainable AI (XAI). Most of the previous research done in patient trajectories are neglecting the data fusion part as well as broadening the scope of the trajectories into other relevant available sources (e.g. self-care which is covered in subject area 3). We will enrich the concept of patient trajectory by exploring and injecting more valuable sources around the patient and disease. XAI can facilitate the process of trust and other issues regarding the "black box" aspects of AI. We aim at leveraging on existing XAI models and scale up them by taking into account the patient trajectory and human-in-the-loop approach involved from the early design steps to the final evaluation phases (covered in subject area 2), which is more or less ignored in general XAI as well as healthcare related XAI methods.
2. Healthcare transformation
There is an increasing awareness in healthcare of the importance of implementation strategies to promote uptake of research and development into routine clinical, organisational, or policy contexts. Although advanced analytics of healthcare data have the potential to transform healthcare through actionable data driven insights, the implementation of AI in healthcare practice is hampered by the lack of implementation strategies that are tailored to the specific settings and contexts for its application. There is a need to close the gap between how work is imagined, and what is actually taking place. This means providing more rigorous and empirical implementation studies of AI in healthcare, underpinning strong theory and real-world understanding. This applies to both the development of patient trajectories based on analysis of healthcare data (covered in subject area 1) and the involvement of relevant stakeholders in the development of new healthcare solutions (covered in subject area 3). Our overall objective is to build an internationally recognised and sustainable AI implementation learning environment and to become leading in the area of AI implementation in healthcare and well known for the quality and relevance of the AI implementation research.
3. Information driven participatory care
The aim of information driven participatory care is to integrate caregivers, patients and technology into efficient, high quality healthcare experiences by creating opportunities to leverage the expertise of each stakeholder in a healthcare journey. While healthcare has been changing, the lack of integration with the existing healthcare system and the paternalistic healthcare model that is prevalent has prevented participatory care from being used to its full potential. The introduction of information driven care enables the use of all available expertise and resources, including intelligent computing, mHealth technologies such as sensors, wearables, digital healthcare apps, and self-care towards increasing the efficiency of the healthcare system while improving healthcare quality by delivering care where and when it is needed the most. Information driven participatory care utilizes patient trajectories (covered in subject area 1) to better match healthcare interventions, including self-care, with patient needs. Healthcare transformation (aubject area 2) is a core aim that creates a healthcare system that inherently utilizes information driven participatory care to provide the best possible care and patient empowerment. The key objectives for information driven participatory care are to define frameworks, design guidelines, design patterns and a case study for information driven participatory care that can be used by private companies as well as public actors in an interconnected ecosystem to leverage participation for increasing efficiency, quality and patient empowerment and satisfaction in healthcare.