
This guide for Medical Clinical Diagnosis and Treatment Oriented Knowledge Graphs (MCKGs) specifies: 1) A construction process for MCKGs, including knowledge acquisition, knowledge representation, knowledge fusion, and knowledge inference of clinical diagnosis and treatment information. 2) Input data requirements, including authoritative data such as medical literature, clinical diagnosis and treatment guides, medical knowledge base, and expert consensus. 3) Functions and interfaces of applications, including knowledge-driven diagnostic decision support, knowledge recommendation, or interpretation of examination report.
- Sponsor Committee
- C/SAB - Standards Activities Board
Learn More - Status
- Active PAR
- PAR Approval
- 2022-02-23
Working Group Details
- Society
- IEEE Computer Society
Learn More - Sponsor Committee
- C/SAB - Standards Activities Board
Learn More - Working Group
-
KG_WG - Knowledge Graph Working Group
Learn More - IEEE Program Manager
- Jonathan Goldberg
Contact - Working Group Chair
- Ruiqi Li
P2807
Framework of Knowledge Graphs
This standard defines the framework of knowledge graphs (KGs). The framework describes the input requirement of KG, construction process of KG, i.e., extraction, storage, fusion and understanding, performance metrics, applications of KG, verticals, KG related artificial intelligence (AI) technologies and other required digital infrastructure.
P2807.4
Guide for Scientific Knowledge Graphs
This guideline for Scientific Knowledge Graphs (SKG) specifies: 1) Data scope, including the actors such as authors or organizations, the documents such as journal or conference publications, and the research knowledge such as research topics or technologies; 2) SKG construction process, including knowledge acquisition, knowledge fusion, knowledge representation, or knowledge inference of scientific knowledge; 3) Applications, including academic service, intelligence mining, or scholar analysis.