Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Logical Scaling in Formal Concept Analysis
ICCS '97 Proceedings of the Fifth International Conference on Conceptual Structures: Fulfilling Peirce's Dream
Towards Representing FCA-based Ontologies in Semantic Web Rule Language
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
Concept Analysis of OWL Ontology Based on the Context Family Model
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
Completing description logic knowledge bases using formal concept analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Formal concept analysis in information science
Annual Review of Information Science and Technology
Query Answering for OWL-DL with rules
Web Semantics: Science, Services and Agents on the World Wide Web
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ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Guest Editorial: Special Issue on Auditing of Terminologies
Journal of Biomedical Informatics
Visual coder: clinical coding in translational research
Proceedings of the 1st ACM International Health Informatics Symposium
Conceptual-driven classification for coding advise in health insurance reimbursement
Artificial Intelligence in Medicine
What's happening in semantic web: and what FCA could have to do with it
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Review: Formal concept analysis in knowledge processing: A survey on applications
Expert Systems with Applications: An International Journal
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Background: With the 11th revision of the International Classification of Disease (ICD) being officially launched by the World Health Organization (WHO), the significance of a formal representation for ICD coding rules has emerged as a pragmatic concern. Objectives: To explore the role of Formal Concept Analysis (FCA) on examining ICD10 coding rules and to develop FCA-based auditing approaches for the formalization process. Methods: We propose a model for formalizing ICD coding rules underlying the ICD Index using FCA. The coding rules are generated from FCA models and represented in the Semantic Web Rule Language (SWRL). Two auditing approaches were developed focusing upon non-disjoint nodes and anonymous nodes manifest in the FCA model. The candidate domains (i.e. any three character code with their sub-codes) of all 22 chapters of the ICD10 2006 version were analyzed using the two auditing approaches. Case studies and a preliminary evaluation were performed for validation. Results: A total of 2044 formal contexts from the candidate domains of 22 ICD chapters were generated and audited. We identified 692 ICD codes having non-disjoint nodes in all chapters; chapters 19 and 21 contained the highest proportion of candidate domains with non-disjoint nodes (61.9% and 45.6%). We also identified 6996 anonymous nodes from 1382 candidate domains. Chapters 7, 11, 13, and 17, have the highest proportion of candidate domains having anonymous nodes (97.5%, 95.4%, 93.6% and 93.0%) while chapters 15 and 17 have the highest proportion of anonymous nodes among all chapters (45.5% and 44.0%). Case studies and a limited evaluation demonstrate that non-disjoint nodes and anonymous nodes arising from FCA are effective mechanisms for auditing ICD10. Conclusion: FCA-based models demonstrate a practical solution for formalizing ICD coding rules. FCA techniques could not only audit ICD domain knowledge completeness for a specific domain, but also provide a high level auditing profile for all ICD chapters.