Struck by OWL: The Adoption of Semantic Web Standards for ICD-11

musen-500x700Mark A. Musen, M.D., Ph.D.
Professor of Medicine (Biomedical Informatics), Stanford University
Director, Stanford WHO Collaborating Center for Classifications, Terminologies, and Standards

Recorded: April 21, 2016

Watch the recorded video
Download slides (PDF)

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

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.