Gamuts

The Gamuts website provides online reference information to link radiology to other Semantic Web resources, including an online quiz-question generator, and a visualization tool.

See also:

Joseph J. Budovec, MD, Cesar A. Lam, MD, Charles E. Kahn, "Informatics in Radiology: Radiology Gamuts Ontology: Differential Diagnosis for the Semantic Web", 'RadioGraphics', January 2014, doi: 10.1148/rg.341135036

Abstract: The Semantic Web is an effort to add semantics, or “meaning,” to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts (www.gamuts.net). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web.

Charles E. Kahn Jr., Joseph J. Budovec, Cesar A. Lam and Stephen Goth, "An Ontology of Differential Diagnosis in Diagnostic Radiology", presented at 2014 AMIA Translational Summit

Abstract: We created an ontology of 282 differential-diagnosis lists, or “gamuts,” in the domain of gastrointestinal radiology. The model describes 7,042 relationships for causality, subsumption, and synonymy among 3,363 disorders and imaging observations; the ontology’s concepts are annotated with and indexed by RadLex® concepts and SNOMED Clinical Terms®. The ontology is published as a Web Ontology Language (OWL) document. The knowledge representation allows automated reasoning over the ontology and integration with heterogeneous biomedical knowledge resources such as decision support systems, clinical image repositories, and the biomedical literature. This ontology has been applied to create several applications, including a RESTful web service, a web-based, illustrated gamuts reference, and a differential-diagnosis quiz generator. The present work serves as a model for a comprehensive ontology of differential diagnosis in diagnostic radiology.