The Digital Pathology Consortium has been established through a Community Research Infrastructure grant from the National Science Foundation. We have been tasked with creating a diverse group of collaborative stakeholders with a common interest in artificially intelligent systems for interpreting digitized pathology slides. Pathology slides are ubiquitous, and are used to diagnose everything from cancer to blood disorders. Considering that hospitals create hundreds of thousands of slides every day, Big Data has a great potential for learning and analyzing these images. The ultimate goal is expedited and improved outcomes for patients.

The National Science Foundation has indicated that it is greatly interested in the tools and technology that a sustained effort in Digital Pathology would create. Our goal is to bring together digital pathology practitioners in medicine, computer science, engineering, and industry. Together, we can pool tools, data, and knowledge in order to accelerate learning in this field.

This effort is led by the Neural Engineering Data Consortium at Temple University (Philadelphia, PA). We have a track record of creating well-curated biomedical data that is shared freely with the research community. We are currently creating a large corpus of well-labeled clinical digital pathology data, ideally-suited for machine learning and image processing practitioners. The data's diversity and scope make it especially challenging for computer pattern matching, and thus an exceptional research challenge.

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