Cancer Treatment Pilot - Greece
The Context
Cancer is a complex disease, encompassing various factors that impact its prevention, progression, treatment, and follow-up. Developing effective decision support tools and AI models for cancer management and prediction requires access to large datasets that encompass multiple levels of data.
However, currently, the necessary data is fragmented across various healthcare silos. In addition to their fragmentation, these datasets often exhibit heterogeneity and data quality issues, hindering their broader utility. Addressing the current challenges in health-related data necessitates breaking down these silos, standardizing, cleaning, and ensuring that data becomes FAIR (Findable, Accessible, Interoperable, and Reusable). Furthermore, ensuring security, visualization, and real-time updates/synchronization are crucial for their effective utilization.
Our Pilot
In our Greek pilot project, we aim to tackle the FAIRification of multimodal cancer data, with a particular focus on improving data collection, storage, and accessibility from diverse sources. To achieve this, we have already developed a Data Innovation Canvas that comprehensively maps out stakeholders, data sources, governance and regulation, available tools, data channels, as well as the added value and business impact.
This canvas serves as a blueprint for creating a data ecosystem that facilitates data collection, cleansing, and FAIRification. We will also provide the necessary tools and APIs for each step of the process, alongside detailed workflows for data import and usage. This approach ensures the seamless collaboration of all stakeholders and regulated access to the collected information.
Benefits
The benefits of data sharing enabled by the Regional Smart Health Data Space (RSHDS) are substantial. We anticipate that this platform will maximize the utility of available data by offering easily accessible, standardized datasets. It enables innovation by making cancer data searchable and reusable for AI modeling and decision support tools. Ultimately, this leads to improved care through data-driven insights, allowing for more efficient planning and decision-making in cancer treatment.
