This recommended practice specifies a framework for knowledge modeling and fusion to enable collaborative analysis of high-throughput medical imaging data. This recommended practice specifies: 1) A knowledge model for the collaborative analysis of high-throughput medical imaging, standardizing the definitions of entity types, inter-entity relationships, and built-in security and privacy attributes. 2) An end-to-end analysis pipeline structured around three key phases: data pre-processing, multi-modal data fusion, and collaboration controlling. 3) Security control interfaces and process to help ensure secure and compliant cross-institutional data utilization.
- Standard Committee
- C/KESC - Knowledge Engineering Standards Committee
- Status
- Active PAR
- PAR Approval
- 2026-06-04
Working Group Details
- Society
- IEEE Computer Society
- Standard Committee
- C/KESC - Knowledge Engineering Standards Committee
- Working Group
-
HIMDA - High-throughput Medical Imaging Data Collaborative Analysis Working Group
- IEEE Program Manager
- Meng Zhao
Contact Meng Zhao - Working Group Chair
- HONGGUANG CHEN
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