There is a plethora of disease ontologies available, all potentially useful for the annotation of biological datasets. We define seven desirable features for such ontologies and examine whether or not these features are supported by eleven disease ontologies. The four ontologies most closely aligned with our desiderata are Disease Ontology, SNOMED CT, NCI thesaurus and UMLS.

Metonymies are language phenomena, in which one expression is used to refer to a related one. Whereas there are many examples in medical discourse, it has been controversially discussed to what extent metonymic phenomena also matter in medical terminologies like SNOMED CT, where they could hamper their proper use. We investigated this by analyzing all SNOMED CT single word fully specified names...

Comprehensive clinical terminologies such as SNOMED CT tend to overlap with specialized terminologies such as LOINC (e.g., for the domain of laboratory procedures). Terminological systems such as the UMLS are often used to bridge between terminologies. However, the integration of LOINC in the UMLS and with other terminologies remains suboptimal. We mapped concepts for laboratory tests from LOIN...

VCM (Visualization of Concept in Medicine) is an iconic language for representing key medical concepts by icons. However, the use of this language with reference terminologies, such as SNOMED CT, will require the mapping of its icons to the terms of these terminologies. Here, we present and evaluate a semi-automatic semantic method for the mapping of SNOMED CT concepts to VCM icons. Both SNOMED...

OBJECTIVE The integration of SNOMED CT into the Unified Medical Language System (UMLS) involved the alignment of two views of synonymy that were different because the two vocabulary systems have different intended purposes and editing principles. The UMLS is organized according to one view of synonymy, but its structure also represents all the individual views of synonymy present in its source ...

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could n...

Methods Inf Med 2012; 51: 529–538 doi: 10.3414/ME11-02-0023 received: August 22, 2011 accepted: May 21, 2012 prepublished: October 1, 2012 Correspondence to: Anne Randorff Højen Department of Health Science and Technology Medical Informatics Aalborg University Fr. Bajers Vej 7 C2 9220 Aalborg ∅ Denmark E-mail: [email protected] specialty Electronic Health Record systems (EHR systems) or just beyo...

Access to reliable data from electronic health records is of high importance in several key areas in patient care, biomedical research, and education. However, many of the clinical entities are negated in the patient record text. Detecting what is a negation and what is not is therefore a key to high quality text mining. In this study we used the NegEx system adapted for Swedish to investigate ...

Objective: To investigate the lexico-syntactic properties of clinical phenotype terms in order to identify partial lexical mappings between HPO and SNOMED CT. Methods: We identify modifiers HPO terms and attempt to map demodified terms to SNOMED CT through UMLS. Results: We identified partial mappings to SNOMED CT for 20% of HPO concepts with no complete mapping to SNOMED CT. Conclusions: Throu...

Relation reversals in ontological systems refer to such patterns as a path from concept A to concept B in one version becoming a path with the position of A and B switched in another version. We present a scalable approach, using cloud computing, to systematically extract all hierarchical relation reversals among 8 SNOMED CT versions from 2009 to 2014. Taking advantage of our MapReduce algorith...