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Updated: Sep 22, 2025
07:50
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
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Semi-Automated Approach to Map Clinical Concepts to SNOMED CT Terms by Using Terminology Server
Abdul Mateen Rajput1, Karen Triep1, Olga Endrich1
1Medical Directorate, Medizincontrolling, Inselspital, University Hospital Bern, Insel Gruppe, Bern, Switzerland.
Studies in Health Technology and Informatics
|May 20, 2022
Summary
Mapping clinical concepts to SNOMED CT is vital for healthcare interoperability. This study explores using the Snowstorm terminology server to automate data retrieval and SNOMED CT mapping, addressing challenges of manual processes.
Area of Science:
- Health Informatics
- Medical Terminology Management
Background:
- Semantic interoperability in healthcare relies on mapping clinical concepts to SNOMED CT.
- Manual SNOMED CT mapping is labor-intensive and prone to errors, hindering efficient data integration.
Purpose of the Study:
- To investigate the feasibility of automating clinical concept data retrieval and SNOMED CT mapping.
- To evaluate the potential of the Snowstorm terminology server for streamlining mapping processes.
Main Methods:
- Utilized Snowstorm, a terminology server developed by SNOMED International.
- Explored Snowstorm's capabilities for automated data retrieval relevant to SNOMED CT mapping.
Main Results:
- Demonstrated the feasibility of using Snowstorm for automated data retrieval.
- Indicated potential for Snowstorm to automate aspects of SNOMED CT mapping.
Conclusions:
- Snowstorm shows promise in automating data retrieval for SNOMED CT mapping.
- Automation using terminology servers like Snowstorm can mitigate challenges associated with manual mapping.
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