Struck by OWL: The Adoption of Semantic Web Standards for ICD-11 -
Yosemite Project Webinar
Mark A. Musen, M.D., Ph.D., Professor of Medicine (Biomedical
Informatics), Stanford University; Director, Stanford WHO Collaborating
Center for Classifications, Terminologies, and Standards
Join the live broadcast: https://goo.gl/OQzDmu
Date: Thursday April 21, 2016
Time: 2:00pm Eastern US timezone
Duration: 1 hour
Download calendar invite:
http://yosemiteproject.org/2016/webinars/musen/calendar-invite.ics
Submit questions by email in advance or during the webinar: da...@dbooth.org
ABSTRACT
Now that the United States has finally transitioned to the 10th revision
of the International Classification of Diseases (ICD-10), we can
anticipate the 11th revision, just around the corner. In developing
ICD-11, the World Health organization is adopting some rather novel
representational choices, including the use of a formal “content model”
to frame the description of each entity in the classification; the
ability to extract views (“linearizations”) from the standard
classification to meet the needs of particular tasks (e.g., representing
morality, representing mortality, coding descriptions for low-resource
settings); the "post-coordination" of terms to simplify the enumeration
of complex expressions; and the adoption of OWL. We will discuss the
design of ICD-11, and what the migration to this next version of ICD
might be like.
ABOUT THE SPEAKER
Mark Musen Dr. Musen is Director of the Stanford University Center for
Biomedical Informatics Research. He conducts research related to
intelligent systems, reusable ontologies, metadata for publication of
scientific data sets, and biomedical decision support. His group
developed Protégé, the world’s most widely used technology for building
and managing terminologies and ontologies. He is principal investigator
of the National Center for Biomedical Ontology, one of the original
National Centers for Biomedical Computing created by the U.S.
National Institutes of Heath (NIH). He also is principal investigator
of the Center for Expanded Data Annotation and Retrieval (CEDAR). CEDAR
is a center of excellence supported by the NIH Big Data to Knowledge
Initiative, with the goal of developing new technology to ease the
authoring and management of biomedical experimental metadata.
