Aim

Owing to the complexity and large size of image data in pathology, artificial intelligence (AI) algorithms preferably run on a dedicated high-performance cluster (HPC). Validation of newly developed algorithms usually requires integration into an image management system (IMS), which is a time-consuming process. We propose an IMS-independent approach to rapidly validate and deploy AI algorithms in research and diagnostic settings (Fig. 1). A generalizable interface for any image-related AI algorithm has been developed to set up an automatic workflow between the institute and the remote HPC. Once image data is generated, the data flow is managed and monitored by a data and job manager communicating with the HPC. A web-based graphical user interface (GUI) displays the status and allows pathologists to visually evaluate the result in a user-friendly manner and provide instant and structured feedback.