Abstract
Applications of deep learning and other artificial intelligence techniques play an increasing role in pathological research. In contrast to research, applications in clinical routine are rare so far, although the first certified solutions have already been established (analysis of prostate sections, ER, PR, and Her2 in breast cancer). Besides the still low use of virtual microscopy in practice, there are anumber of hurdles that stand in the way of arapid diffusion of AI applications. The EMPAIA project has a goal of removing these hurdles. The path taken to build an ecosystem for this purpose is intended to exemplify that the introduction of AI applications in image-based diagnostics is possible on abroad basis if the existing hurdles are removed in ajoint, moderated process. The components of the EMPAIA ecosystem and its strategy will be described, and reference will be made to the technical solution approaches.
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