ArticleInsights into imaging2025
RadLex and SNOMED CT integration: a pilot study for standardising radiology classification.
Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Foundation models in biomedical imaging: turning hype into reality.Nature biomedical engineering · 2026Review
- Large language models for structuring knee ultrasound reports-A comparative evaluation of DeepSeek R1, gemini 2.5 flash, and GPT-4o.BMC medical informatics and decision making · 2026Article
- Interoperability of health data using FHIR Mapping Language: transforming HL7 CDA to FHIR with reusable visual components.Frontiers in digital health · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEffective communication and information exchange across diverse platforms are critical in healthcare data systems. However, the presence of multiple coding systems and varying standards creates discrepancies and misalignments, highlighting the need for innovative solutions to address these challenges.
objectiveThe study aimed to develop a technical and semantic interoperability method specifically for radiology procedures, utilising the terminology management tool TermX to facilitate efficient data exchange and utilisation in healthcare.
resultsThe study resulted in a revised RadLex data model using SNOMED CT, accompanied by a mapping guide and a classification system for X-ray and angiography procedures. This classification system consists of nineteen distinct properties, each defined by specific value sets derived from SNOMED CT terminology. A total of 380 concepts were utilised to describe the 622 procedures examined comprehensively.
conclusionThrough twelve design cycles involving in-depth analysis and iterative refinement, the mapping of angiography and X-ray procedures was successfully achieved, culminating in the creation and validation of a universal model that enhances both primary and secondary data collection. The efficacy and innovation of this system pave the way for further advancements in healthcare interoperability. CRITICAL RELEVANCE STATEMENT: The innovative integration achieved in this study for standardising radiology classification promises to improve data management practices and enhance patient care outcomes through increased interoperability within the healthcare sector. KEY POINTS: A universal radiology procedure model to enhance capture would be valuable. A tool to facilitate technical and semantic interoperability for efficient data exchange in healthcare was created. This system could pave the way for futher advancements in healthcare interoperability.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.