Motivation: SNOMED CT provides about 300,000 codes with fine-grained definitions to support interoperability of health data. However, even experienced human coders tend to disagree about which codes to choose for expressing clinical content. Results: 20 short clinical text fragments were independently annotated with SNOMED CT codes by two terminology experts. We analysed each disagreement insta...

With many hospitals digitalizing clinical records it has opened opportunities for researchers in NLP, Machine Learning to apply techniques for extracting meaning and make actionable insights. There has been previous attempts in mapping free text to medical nomenclature like UMLS, SNOMED. However, in this paper, we analyzed diagnosis in clinical reports by mapping into ICD10 codes. We propose a ...

OBJECTIVE To evaluate the utility of SNOMED RT in support of a natural language interface for encoding of clinical assessments. METHOD Using a random sample of clinical terms from the UNMC Lexicon, I mapped the terminology into canonical data entries using SNOMED RT. Working from the source term language, I evaluated lexical mapping to the SNOMED term set, and the function of the SNOMED RT se...

The NIH roadmap endorses the use of data standards in clinical research that are compatible with health care data standards. To facilitate standards use, members of the Rare Disease Clinical Research Network have developed tools to support study investigators and research staff to code clinical research data using SNOMED CT at the point of research. This tool is customized to help the user will...

Medical Language Processing (MLP), especially in specific domains, requires fine-grained semantic lexica. We examine whether robust natural language processing tools used on a representative corpus of a domain help in building and refining a semantic categorization. We test this hypothesis with ZELLIG, a corpus analysis tool. The first clusters we obtain are consistent with a model of the domai...

BACKGROUND Procedures documented by general practitioners in primary care have not been studied in relation to procedure coding systems. We aimed to describe procedures documented by Swedish general practitioners in electronic patient records and to compare them to the Swedish Classification of Health Interventions (KVÅ) and SNOMED CT. METHODS Procedures in 200 record entries were identified,...

Veterans Health Administration (VHA) is now evaluating use of SNOMED-CT. This paper reports the first phase of this evaluation, which examines the coverage of SNOMED-CT for problem list entries. Clinician expressions in VA problem lists are quite diverse compared to the content of the current VA terminology Lexicon. We selected a random set of 5054 narratives that were previously "unresolved" a...

Morphological knowledge is useful for medical language processing, information retrieval and terminology or ontology development. We show how a large volume of morphological associations between words can be learnt from existing medical terminologies by taking advantage of the semantic relations already encoded between terms in these terminologies: synonymy, hierarchy and transversal relations....

Several clinical terminologies now utilize description logic to model the logical definitions of concepts. Recent editions of the Systematized Nomenclature of Medicine (SNOMED) have been developed using the description logic Ontylog. A significant design criterion for SNOMED is to keep concept expressions simple enough to be broadly usable by clinicians, while maintaining faithful representatio...