Context-based ontology building support in clinical domains using formal concept analysis
Objective: Ontology in clinical domains is becoming a core research field in the realm of medical informatics. The objective of this study is to explore the potential role of formal concept analysis (FCA) in a context-based ontology building support in a clinical domain (e.g. cardiovascular medicine here). Methodology: We developed an ontology building support system that integrated an FCA module with a natural language processing (NLP) module. The user interface of the system was developed as a Protg-2000 JAVA tab plug-in. A collection of 368 textual discharge summaries and a standard dictionary of Japanese diagnostic terms (MEDIS ver2.0) were used as the main knowledge sources. A preliminary evaluation was taken to show the usefulness of the system. Results: Stability was shown on the MEDIS-based medical concept extraction with high precision. 7314% (meanS.D.) of the compound medical phrases extracted were sufficiently meaningful to form a medical concept from a clinical perspective. Also, 57.7% of attribute implication pairs (i.e. medical concept pairs) extracted were identified as positive from a clinical perspective. Conclusion: Under the framework of our ontology building support system using FCA, the clinical experts could reach a mass of both linguistic information and context-based knowledge that was demonstrated as useful to support their ontology building tasks.
formal concept analysis natural language processing knowledge representation information retrieval medical records knowledge acquisition