ChainCatcher message, Codatta and DPath.ai have teamed up to release an optimized version of the TCGA PRAD dataset. Through the Codatta platform, global pathology experts are invited to participate, elevating traditional slide-level labeling to ROI area-level spatial annotations, significantly improving the accuracy, detail, and transparency of diagnoses.
This collaborative project processed 435 whole slide images, optimized 245 cases, and confirmed the accuracy of 190 annotations, providing essential resources for AI model training and pathology research. Codatta's Royalty Model allows contributors to retain data ownership and earn ongoing revenue through data value growth, while offering broader data access opportunities for small and medium-sized AI startups.
This project demonstrates the potential of decentralized and community-driven solutions in advancing medical AI innovation, highlighting the leadership of Codatta and DPath.ai in the creation of high-quality data.