Your browser doesn't support javascript.
loading
Ontologies in the New Computational Age of Radiology: RadLex for Semantics and Interoperability in Imaging Workflows.
Chepelev, Leonid L; Kwan, David; Kahn, Charles E; Filice, Ross W; Wang, Kenneth C.
Afiliação
  • Chepelev LL; From the Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto General Hospital, 585 University Ave, 1-PMB 286, Toronto, ON, Canada M5G 2N2 (L.L.C.); Insygnia Consulting, Toronto, ON, Canada (D.K.); Department of Radiology, Perelman School of Medicine, Univer
  • Kwan D; From the Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto General Hospital, 585 University Ave, 1-PMB 286, Toronto, ON, Canada M5G 2N2 (L.L.C.); Insygnia Consulting, Toronto, ON, Canada (D.K.); Department of Radiology, Perelman School of Medicine, Univer
  • Kahn CE; From the Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto General Hospital, 585 University Ave, 1-PMB 286, Toronto, ON, Canada M5G 2N2 (L.L.C.); Insygnia Consulting, Toronto, ON, Canada (D.K.); Department of Radiology, Perelman School of Medicine, Univer
  • Filice RW; From the Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto General Hospital, 585 University Ave, 1-PMB 286, Toronto, ON, Canada M5G 2N2 (L.L.C.); Insygnia Consulting, Toronto, ON, Canada (D.K.); Department of Radiology, Perelman School of Medicine, Univer
  • Wang KC; From the Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto General Hospital, 585 University Ave, 1-PMB 286, Toronto, ON, Canada M5G 2N2 (L.L.C.); Insygnia Consulting, Toronto, ON, Canada (D.K.); Department of Radiology, Perelman School of Medicine, Univer
Radiographics ; 43(3): e220098, 2023 03.
Article em En | MEDLINE | ID: mdl-36757882
ABSTRACT
From basic research to the bedside, precise terminology is key to advancing medicine and ensuring optimal and appropriate patient care. However, the wide spectrum of diseases and their manifestations superimposed on medical team-specific and discipline-specific communication patterns often impairs shared understanding and the shared use of common medical terminology. Common terms are currently used in medicine to ensure interoperability and facilitate integration of biomedical information for clinical practice and emerging scientific and educational applications alike, from database integration to supporting basic clinical operations such as billing. Such common terminologies can be provided in ontologies, which are formalized representations of knowledge in a particular domain. Ontologies unambiguously specify common concepts and describe the relationships between those concepts by using a form that is mathematically precise and accessible to humans and machines alike. RadLex® is a key RSNA initiative that provides a shared domain model, or ontology, of radiology to facilitate integration of information in radiology education, clinical care, and research. As the contributions of the computational components of common radiologic workflows continue to increase with the ongoing development of big data, artificial intelligence, and novel image analysis and visualization tools, the use of common terminologies is becoming increasingly important for supporting seamless computational resource integration across medicine. This article introduces ontologies, outlines the fundamental semantic web technologies used to create and apply RadLex, and presents examples of RadLex applications in everyday radiology and research. It concludes with a discussion of emerging applications of RadLex, including artificial intelligence applications. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiologia / Ontologias Biológicas Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiologia / Ontologias Biológicas Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article