Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

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.

[1]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[2]  Daniel L. Rubin,et al.  Creating and Curating a Terminology for Radiology: Ontology Modeling and Analysis , 2008, Journal of Digital Imaging.

[3]  Richard N. Taylor,et al.  Principled design of the modern Web architecture , 2002, TOIT.

[4]  Natalya F. Noy,et al.  Protégé: A Tool for Managing and Using Terminology in Radiology Applications , 2007, Journal of Digital Imaging.

[5]  Christopher G. Chute,et al.  BioPortal: ontologies and integrated data resources at the click of a mouse , 2009, Nucleic Acids Res..

[6]  Csongor Nyulas,et al.  BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications , 2011, Nucleic Acids Res..

[7]  Ralph Weissleder,et al.  Primer of Diagnostic Imaging , 1994 .

[8]  Jamie Giesbrandt,et al.  Radiology Review Manual, 7th ed. , 2012 .

[9]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[10]  Tim Berners-Lee,et al.  Publishing on the semantic web , 2001, Nature.

[11]  Martin Kuiper,et al.  Biological knowledge management: the emerging role of the Semantic Web technologies , 2009, Briefings Bioinform..

[12]  Paul T. Groth,et al.  A Semantic Web Primer. - 3rd ed. , 2012, CoopIS 2012.

[13]  José L. V. Mejino,et al.  A reference ontology for biomedical informatics: the Foundational Model of Anatomy , 2003, J. Biomed. Informatics.

[14]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[15]  Lee Feigenbaum,et al.  The Semantic Web in action. , 2007, Scientific American.

[16]  Fred Prior Medical knowledge discovery and management. , 2009, Military medicine.

[17]  Charles E. Kahn,et al.  Dynamic “Inline” Images: Context-Sensitive Retrieval and Integration of Images into Web Documents , 2008, Journal of Digital Imaging.

[18]  Jane Hunter,et al.  The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain , 2011, BMC Bioinformatics.

[19]  Thomas Lukasiewicz Probabilistic description logic programs , 2007, Int. J. Approx. Reason..

[20]  K. Cheung,et al.  Semantic Web for Health Care and Life Sciences: a review of the state of the art , 2009, Briefings Bioinform..

[21]  A. Rector,et al.  Relations in biomedical ontologies , 2005, Genome Biology.

[22]  H. Lowe,et al.  Understanding and using the medical subject headings (MeSH) vocabulary to perform literature searches. , 1994, JAMA.

[23]  R. Lachman Taybi and Lachman’s radiology of syndromes, metabolic disorders and skeletal dysplasias , 2006, La radiologia medica.

[24]  E. Burnside,et al.  Toward best practices in radiology reporting. , 2009, Radiology.