The main aim AIMed is to promote the use of Artificial Intelligence (AI) and High Performance Computing (HPC) platforms for harvesting knowledge from large collections of heterogeneous medical data (health records, multi-modal medical imaging and medical sensor data, etc.) distributed over different locations (different institutions in different countries) in a holistic approach (from data acquisition protocols, data structures, storage formats, processing and analysis methods, as well as computing algorithms and hardware platforms), to develop a new generation of knowledge-driven Clinical Decision Support Systems (CDSS). These new systems have high-potential to improve the quality of healthcare by reducing medical errors and cutting costs. For that end, future CDSS need to move from being data-driven to being knowledge-driven systems, through capture, abstraction and use of clinical knowledge and medical Big Data (BD) collections. A necessary step to achieve this is the establishment of an interdisciplinary network of researchers and institutions from academia, industry and public sector to leverage research results and facilitate exchange and use of BD collections scattered across borders and systems. The network will thus raise the awareness about this field and foster the creation of new knowledge and the development of novel approaches in AI, BD, HPC for CDSS through networking and training of ECIs and engagement of different stakeholder including policy makers, user groups, and general public. Furthermore, it will educate a generation of experts with a new scientific mindset to improve competitiveness of European institutions and their innovation capabilities.
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