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[Research on Construction of Knowledge Base for MRI Equipment Maintenance Based on Knowledge Graph]
Chengchen Chu1, Zhiyong Ji1, Bin Li1
1Department of Medical Equipment, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233.
Summary
This study introduces a knowledge graph-based system for dynamic fault repair of magnetic resonance imaging (MRI) equipment. It enhances medical equipment management and intelligent hospital construction through improved maintenance efficiency.
Area of Science:
- Medical Equipment Management
- Knowledge Graph Technology
- Intelligent Systems
Context:
- Modern hospital management requires efficient medical equipment maintenance systems.
- Large medical equipment, such as MRI, presents unique maintenance challenges.
- Existing systems may lack dynamic and interactive capabilities for fault repair.
Purpose:
- To propose a dynamic interactive fault repair knowledge base system for MRI equipment.
- To leverage knowledge graph technology for intelligent medical equipment management.
- To enhance the scientific and effective maintenance guarantee system for hospital equipment.
Summary:
- A knowledge base system for magnetic resonance imaging (MRI) equipment fault repair was constructed using knowledge graph technology.
- Actual maintenance data was collected and organized to build the knowledge base.
- Initial functions include fault information retrieval, technical guidance, and training for MRI equipment maintenance.
Impact:
- Provides an objective basis for decision-making in large medical equipment maintenance.
- Enhances the efficiency of fault repair and maintenance processes.
- Elevates the development level of intelligent hospitals through improved equipment management.
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