Computer-based medical terminology and knowledge representation.

Area of Science:

• Medical Informatics
• Computational Linguistics
• Knowledge Representation

Background:

• Current medical terminologies lack a unified, meaning-based organizational structure.
• Efficient coding and retrieval of medical information are crucial for healthcare.
• Existing systems may present challenges in achieving global compatibility.

Purpose of the Study:

• To present a novel computer-based medical terminology.
• To describe a unique systematization of terms based on semantic similarity.
• To propose a standardized coding method using semantic addresses for global use.

Main Methods:

• Construction of a large-scale (140,000 terms) medical terminology.
• Systematization of terms into a single hierarchical tree using semantic similarity as the key attribute.
• Development of a term typing system based on knowledge patterns and relationships (arcs) between terms (nodes).
• Definition of a 'semantic address' based on a term's position within the hierarchy for coding.

Main Results:

• A hierarchical medical terminology of approximately 140,000 terms was created.
• The systematization resulted in a single, unified hierarchical tree structure.
• Six distinct types of medical terms were identified based on their knowledge patterns.
• A coding system, the 'semantic address', was derived from the hierarchical position.

Conclusions:

• The developed computer-based medical terminology offers a structured, meaning-based approach.
• The semantic address system provides a novel method for medical term coding.
• The semantic address is recommended for achieving worldwide compatibility in medical terminology and coding.