Overlapping Complex Concepts Have More Commission Errors, Especially in Intensive Terminology Auditing.

SNOMED CT is a large, complex and widely-used terminology. Auditing is part of the life cycle of terminologies. A review of terminologies' content can identify two error categories: commission errors, such as an incorrect parent or attribute relationship, indicating errors in a concept's modeling, and omission errors, such as missing a parent or attribute relationship, representing incomplete modeling of a concept.

Mining non-lattice subgraphs for detecting missing hierarchical relations and concepts in SNOMED CT.

Objective: Quality assurance of large ontological systems such as SNOMED CT is an indispensable part of the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery of missing hierarchical relations and concepts in SNOMED CT.

Material And Methods: All non-lattice subgraphs (the structural part) in SNOMED CT are exhaustively extracted using a scalable MapReduce algorithm.

Tracking the Remodeling of SNOMED CT's Bacterial Infectious Diseases.

SNOMED CT's content undergoes many changes from one release to the next. Over the last year SNOMED CT's Bacterial infectious disease subhierarchy has undergone significant editing to bring consistent modeling to its concepts. In this paper we analyze the stated and inferred structural modifications that affected the Bacterial infectious disease subhierarchy between the Jan 2015 and Jan 2016 SNOMED CT releases using a two-phased approach.

Analyzing structural changes in SNOMED CT's Bacterial infectious diseases using a visual semantic delta.

Thousands of changes are applied to SNOMED CT's concepts during each release cycle. These changes are the result of efforts to improve or expand the coverage of health domains in the terminology. Understanding which concepts changed, how they changed, and the overall impact of a set of changes is important for editors and end users.

Extending the coverage of phenotypes in SNOMED CT through post-coordination.

Objectives: To extend the coverage of phenotypes in SNOMED CT through post-coordination.

Methods: We identify frequent modifiers in terms from the Human Phenotype Ontology (HPO), which we associate with templates for post-coordinated expressions in SNOMED CT.

Results: We identified 176 modifiers, created 12 templates, and generated 1,617 post-coordinated expressions.

Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies.

Objective: Standards terminologies may be large and complex, making their quality assurance challenging. Some terminology quality assurance (TQA) methodologies are based on abstraction networks (AbNs), compact terminology summaries. We have tested AbNs and the performance of related TQA methodologies on small terminology hierarchies.

A tribal abstraction network for SNOMED CT target hierarchies without attribute relationships.

Objective: Large and complex terminologies, such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), are prone to errors and inconsistencies. Abstraction networks are compact summarizations of the content and structure of a terminology. Abstraction networks have been shown to support terminology quality assurance.

Fatal musculoskeletal injuries of Quarter Horse racehorses: 314 cases (1990-2007).

Objective: To determine major causes of death and the anatomic location of musculoskeletal injuries in Quarter Horse racehorses in California.

Design: Retrospective case series.

Animals: 314 Quarter Horse racehorses with musculoskeletal injuries that were necropsied through the California Horse Racing Board Postmortem Program from 1990 to 2007.

Auditing complex concepts of SNOMED using a refined hierarchical abstraction network.

Auditors of a large terminology, such as SNOMED CT, face a daunting challenge. To aid them in their efforts, it is essential to devise techniques that can automatically identify concepts warranting special attention. "Complex" concepts, which by their very nature are more difficult to model, fall neatly into this category.

Assessment of the quality of multi-institutional data for population-based epidemiological studies: a case study of atoxoplasmosis in Bali mynahs (Leucopsar rothschildi).

To evaluate the potential to conduct population-based epidemiologic studies using multi-institutional data, the quality of data extracted from the MedARKS system was evaluated with regard to atoxoplasmosis in Bali mynahs (Leucopsar rothschildi). Data extracted for 338 Bali mynahs from 34 institutions were analyzed for completeness, correctness, and consistency and subjectively analyzed for accessibility. Data completeness was ascertained by analysis of missing records, tests, and blank fields.

Association between findings on palmarodorsal radiographic images and detection of a fracture in the proximal sesamoid bones of forelimbs obtained from cadavers of racing Thoroughbreds.

Objective: To determine the distribution for limbs and bones in horses with fractures of the proximal sesamoid bones and relationships with findings on palmarodorsal radiographic images.

Sample Population: Proximal sesamoid bones obtained from both forelimbs of cadavers of 328 racing Thoroughbreds.

Procedure: Osteophytes; large vascular channels; and fracture location, orientation, configuration, and margin distinctness were categorized by use of high-detail contact palmarodorsal radiographs.

Time-space clustering of human brucellosis, California, 1973-1992.

Infection with Brucella spp. continues to pose a human health risk in California despite great strides in eradicating the disease from domestic animals. Clustering of human cases in time and space has important public health implications for understanding risk factors and sources of infection.

Perceptions of state public health officers and state veterinarians regarding risks of bioterrorism in the United States.

Objective: To assess perceptions of state public health officers and state veterinarians in the United States regarding the risks of bioterrorism and determine the degree of support provided for activities related to bioterrorism.

Design: Cross-sectional survey.

Sample Population: State public health officers and state veterinarians.