A Semi-automated Method for Domain-Specific Ontology Creation from Medical Guidelines
Omar ElAssy, Rik de Vendt, Fabiano Dalpiaz, Sjaak Brinkkemper

TL;DR
This paper presents a semi-automated approach to generate domain-specific medical ontologies from guidelines, enhancing automated medical conversation summarization by capturing guideline-specific knowledge.
Contribution
It introduces a novel semi-automated method to create a Medical Guideline Ontology from SNOMED CT and medical guidelines, tailored for consultation interpretation.
Findings
Successfully created an MGO for Otitis Externa
Demonstrated the method's applicability to real medical guidelines
Improved interpretation of medical consultations
Abstract
The automated capturing and summarization of medical consultations has the potential to reduce the administrative burden in healthcare. Consultations are structured conversations that broadly follow a guideline with a systematic examination of predefined observations and symptoms to diagnose and treat well-defined medical conditions. A key component in automated conversation summarization is the matching of the knowledge graph of the consultation transcript with a medical domain ontology for the interpretation of the consultation conversation. Existing general medical ontologies such as SNOMED CT provide a taxonomic view on the terminology, but they do not capture the essence of the guidelines that define consultations. As part of our research on medical conversation summarization, this paper puts forward a semi-automated method for generating an ontological representation of a medical…
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Taxonomy
Topicslinguistics and terminology studies · Biomedical Text Mining and Ontologies · Clinical practice guidelines implementation
