Medical trauma data authenticity monitoring method and system based on knowledge graph
By using a knowledge graph-based multi-hop diffusion model, chain anomalies in medical data are identified and located, solving the problems of cross-field logical contradictions and semantic inconsistencies in existing technologies, and achieving high-precision data authenticity monitoring and intelligent correction suggestions.
CN122432936APending Publication Date: 2026-07-21北京紫云智能科技有限公司
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 北京紫云智能科技有限公司
- Filing Date
- 2026-05-25
- Publication Date
- 2026-07-21
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Figure CN122432936A_ABST
Abstract
The application provides a medical trauma data authenticity monitoring method and system based on a knowledge graph, and relates to the technical field of medical data processing, comprising the application. The application can effectively identify strong dependence fields by constructing a medical knowledge graph and extracting field combination rules, construct a field dependence graph, and filter effective dependence chains, so as to locate a linked abnormal field cluster. For the abnormal field cluster, the associated path integrity score is calculated by searching for reference cases and weighted matching, and the optimal correction suggestion is output to monitor the authenticity of medical data, accurately locate and correct abnormal data, and improve the data quality and reliability.
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