Roldán-García María Del Mar, García-Godoy María Jesús, Aldana-Montes José F
Ada Byron Research Center, University of Malaga, Ampliación del Campus de Teatinos, Málaga, Spain.
IBIMA Instituto de Investigación Biomédica de Málaga, University of Malaga, Málaga, Spain.
J Biomed Semantics. 2016 Oct 13;7(1):62. doi: 10.1186/s13326-016-0105-x.
Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) has been designed as standard clinical terminology for annotating Electronic Health Records (EHRs). EHRs textual information is used to classify patients' diseases into an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) category (usually by an expert). Improving the accuracy of classification is the main purpose of using ontologies and OWL representations at the core of classification systems. In the last few years some ontologies and OWL representations for representing ICD-10-CM categories have been developed. However, they were not designed to be the basis for an automatic classification tool nor do they model ICD-10-CM inclusion terms as Web Ontology Language (OWL) axioms, which enables automatic classification. In this context we have developed Dione, an OWL representation of ICD-10-CM.
Dione is the first OWL representation of ICD-10-CM, which is logically consistent, whose axioms define the ICD-10-CM inclusion terms by means of a methodology based on SNOMED CT/ICD-10-CM mappings. The ICD-10-CM exclusions are handled with these mappings. Dione currently contains 391,669 classes, 391,720 entity annotation axioms and 11,795 owl:equivalentClass axioms which have been constructed using 104,646 relationships extracted from the SNOMED CT/ICD-10-CM and BioPortal mappings included in Dione using the owl:intersectionOf and the owl:someValuesFrom statements. The resulting OWL representation has been classified and its consistency tested with the ELK reasoner. We have also taken three clinical records from the Virgen de la Victoria Hospital (Málaga, Spain) which have been manually annotated using SNOMED CT. These annotations have been included as instances to be classified by the reasoner. The classified instances show that Dione could be a promising ICD-10-CM OWL representation to support the classification of patients' diseases.
Dione is a first step towards the automatic classification of patients' diseases by using SNOMED CT annotations embedded in Electronic Health Records (EHRs). The purpose of Dione is to standardise and formalise a medical terminology, thereby enabling new kinds of tools and new sets of functionalities to be developed. This in turn assists health specialists by providing classified information from EHRs and enables the automatic annotation of patients' diseases with ICD-10-CM codes.
医学系统命名法 - 临床术语（SNOMED CT）已被设计为用于注释电子健康记录（EHR）的标准临床术语。EHR的文本信息用于将患者疾病分类到《国际疾病分类第十次修订本，临床修订版》（ICD - 10 - CM）类别中（通常由专家进行）。提高分类准确性是在分类系统核心使用本体和OWL表示的主要目的。在过去几年中，已经开发了一些用于表示ICD - 10 - CM类别的本体和OWL表示。然而，它们并非设计用作自动分类工具的基础，也未将ICD - 10 - CM包含术语建模为Web本体语言（OWL）公理，而OWL公理可实现自动分类。在此背景下，我们开发了Dione，一种ICD - 10 - CM的OWL表示。
Dione是ICD - 10 - CM的首个OWL表示，逻辑上是一致的，其公理通过基于SNOMED CT/ICD - 10 - CM映射的方法定义ICD - 10 - CM包含术语。ICD - 10 - CM的排除项通过这些映射来处理。Dione目前包含391,669个类、391,720个实体注释公理和11,795个owl:equivalentClass公理，这些公理是使用从Dione中包含的SNOMED CT/ICD - 10 - CM和BioPortal映射中提取的104,646个关系，通过owl:intersectionOf和owl:someValuesFrom语句构建的。生成的OWL表示已进行分类，并使用ELK推理器测试了其一致性。我们还从西班牙马拉加的维多利亚圣母医院获取了三份临床记录，这些记录已使用SNOMED CT进行了人工注释。这些注释已作为实例包含在内，供推理器进行分类。分类后的实例表明，Dione可能是一种有前景的ICD - 10 - CM OWL表示，可支持患者疾病的分类。
Dione是朝着利用嵌入电子健康记录（EHR）中的SNOMED CT注释对患者疾病进行自动分类迈出的第一步。Dione的目的是使医学术语标准化和形式化，从而能够开发新型工具和新的功能集。这反过来通过提供来自EHR的分类信息帮助健康专家，并能够使用ICD - 10 - CM代码对患者疾病进行自动注释。
