Related Experiment Video
Updated: Jan 13, 2026

03:58
Enhancing Electrode Location Assessment in Cochlear Implantation via Computed Tomography Image Fusion
Published on: January 17, 2025
789
ECLed- a tool supporting the effective use of the SNOMED CT Expression Constraint Language
Tessa Ohlsen1,2, André Sander3, Josef Ingenerf4
1Institute of Medical Biometry and Statistics, Section for Clinical Research IT, University of Luebeck, University Hospital Schleswig-Holstein, Ratzeburger Allee 160, 23562, Luebeck, Germany. ecled.authors@gmail.com.
Journal of Biomedical Semantics
|January 6, 2026
Summary
ECLed simplifies complex SNOMED CT Expression Constraint Language (ECL) queries for non-technical users. This web-based tool enhances clinical research and data analysis by abstracting ECL syntax and the SNOMED CT Concept Model.
Area of Science:
- Medical Informatics
- Clinical Data Management
- SNOMED CT Ontology
Background:
- Expression Constraint Language (ECL) is vital for SNOMED CT semantic queries.
- ECL's complexity hinders adoption in clinical research and analytics.
- Non-experts face challenges with ECL syntax and the SNOMED CT Concept Model.
Purpose of the Study:
- Introduce ECLed, a web-based tool to simplify ECL query creation.
- Enable non-technical users to create and modify ECL queries.
- Facilitate querying of SNOMED CT-coded patient data.
Main Methods:
- Developed ECLed based on detailed functional and non-functional requirements.
- Integrated a processed SNOMED CT Concept Model and FHIR terminology services for validation.
- Utilized a modular architecture with Angular frontend and Spring Boot backend via RESTful interfaces.
Main Results:
- ECLed demonstrated high usability in user surveys.
- Technical validation confirmed reliable generation and editing of complex ECL queries.
- Successfully integrated into the DaWiMed research platform, improving clinical analysis workflows.
Conclusions:
- ECLed abstracts ECL syntax and SNOMED CT Concept Model complexity.
- Provides a user-friendly interface for both technical and non-technical users.
- Optimizes clinical research and data analysis workflows with potential for further integration.

