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Updated: Jun 26, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

A Semantic Web-based System for Managing Clinical Archetypes.

Jesualdo Tomas Fernandez-Breis¹, Marcos Menarguez-Tortosa, Catalina Martinez-Costa

¹Universidad de Murcia, Spain. jfernand@um.es

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 24, 2009

Summary

This summary is machine-generated.

This study presents a Semantic Web System for Managing Archetypes, enhancing clinical knowledge sharing and healthcare information system interoperability. The system supports semantic annotation and searching for ISO13606 and OpenEHR archetypes.

Related Experiment Videos

Last Updated: Jun 26, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

Health Informatics
Computer Science
Semantic Web Technologies

Background:

Archetypes are crucial for sharing clinical knowledge and achieving interoperability in healthcare information systems.
Existing systems may lack robust semantic capabilities for managing archetypes.

Purpose of the Study:

To present a Semantic Web System for Managing Archetypes.
To enable semantic annotation and searching of archetypes.
To support interoperability between healthcare information systems.

Main Methods:

Development of a Semantic Web System tailored for archetype management.
Implementation of semantic annotation functionalities.
Integration of semantic search capabilities.
Compatibility testing with ISO13606 and OpenEHR standards.

Main Results:

The developed system facilitates semantic annotation of archetypes.
The system enables efficient semantic searching of archetypes.
The system demonstrates compatibility with both ISO13606 and OpenEHR archetypes.

Conclusions:

The presented Semantic Web System effectively manages archetypes.
The system enhances clinical knowledge sharing and healthcare interoperability.
The system provides a foundation for advanced semantic querying of clinical data.