Representing the International Classification of Diseases Version 10 in OWL

Current efforts in the biomedical ontology community focus on establishing interoperability and data integration. In covering human diseases, one of the major international standards in clinical practice is the International Classification for Diseases (ICD), maintained by the World Health Organization (WHO). Several countryand language-specific adaptations exist which share the general structure of the WHO version but differ in certain details. This complicates the exchange of patient records and hampers data integration across language borders. We present our approach for modeling the hierarchy of the ICD-10 using the Web Ontology Language (OWL). Our model captures the hierarchical information of the ICD-10 as well as comprehensive class labels for English and German. Specialties such as “Exclusion” statements, which make statements about the disjointness of certain ICD-10 categories, are modeled in a formal way. For properties which exceed the expressivity of OWL-DL, we provide a separate OWL-Full component which allows us to use the hierarchical knowledge and class labels with existing OWL-DL reasoners and capture the additional information in a machine-interpretable way.

[1]  Joachim Dudeck,et al.  XML representation of hierarchical classification systems: from conceptual models to real applications , 2002, AMIA.

[2]  Raphael Volz,et al.  Cooking the Semantic Web with the OWL API , 2003, SEMWEB.

[3]  Olivier Bodenreider,et al.  The Unified Medical Language System (UMLS): integrating biomedical terminology , 2004, Nucleic Acids Res..

[4]  Richard Lenz,et al.  Information Management in Distributed Healthcare Networks , 2005, Data Management in a Connected World.

[5]  Yarden Katz,et al.  Pellet: A practical OWL-DL reasoner , 2007, J. Web Semant..

[6]  Franz Baader,et al.  SNOMED CT's Problem List: Ontologists' and Logicians' Therapy Suggestions , 2007, MedInfo.

[7]  Paul Buitelaar,et al.  Medical Image Understanding Through the Integration of Cross-Modal Object Recognition with Formal Domain Knowledge , 2008, HEALTHINF.

[8]  Daniel L. Rubin,et al.  Translating the Foundational Model of Anatomy into OWL , 2008, J. Web Semant..

[9]  Luciano Serafini,et al.  Logical Analysis of Mappings between Medical Classification Systems , 2008, AIMSA.

[10]  Pinar Wennerberg Aligning Medical Domain Ontologies for Clinical Query Extraction , 2009, EACL.

[11]  Saikat Mukherjee,et al.  Context-Driven Ontological Annotations in DICOM Images - Towards Semantic Pacs , 2009, HEALTHINF.

[12]  Pinar Wennerberg,et al.  A Linguistic Approach to Aligning Representations of Human Anatomy and Radiology , 2009 .

[13]  Franz Baader,et al.  SNOMED reaching its adolescence: Ontologists' and logicians' health check , 2009, Int. J. Medical Informatics.

[14]  Paul Buitelaar,et al.  Pillars of Ontology Treatment in the Medical Domain , 2009, J. Cases Inf. Technol..

[15]  Daniel Sonntag,et al.  Ontologies and Adaptivity in Dialogue for Question Answering , 2010, Studies on the Semantic Web.