Mark A. Musen

Mark A. Musen, MD, PhD

Mark A. Musen, MD, PhD

  • Professor of Medicine (Biomedical Informatics Research) and Biomedical Data Science
  • Stanford Health Policy Associate

Center for Biomedical Informatics Research
Stanford University School of Medicine
1261 Welch Road, MSOB X-215
Stanford, California 94305-5479

(650) 725-3390 (voice)

Biography

Dr. Musen is Professor of Biomedical Informatics and of Biomedical Data Science, and Director of the Stanford Center for Biomedical Informatics Research.  Dr. Musen 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 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.  Dr. Musen directs the World Health Organization Collaborating Center for Classification, Terminology, and Standards at Stanford University, which has developed much of the information infrastructure for the authoring and management of the 11th edition of the International Classification of Diseases (ICD-11). 

publications

Journal Articles
December 2006

Use of Declarative Statements in Creating and Maintaining Computer-Interpretable Knowledge Bases for Guideline-Based Care

Author(s)
cover link Use of Declarative Statements in Creating and Maintaining Computer-Interpretable Knowledge Bases for Guideline-Based Care
Journal Articles
December 2006

Identifying Barriers to Hypertension Guideline Adherence Using Clinician Feedback at the Point of Care

Author(s)
cover link Identifying Barriers to Hypertension Guideline Adherence Using Clinician Feedback at the Point of Care
Journal Articles
December 2004

An intelligent case-adjustment algorithm for the automated design of population-based quality auditing protocols

Author(s)
cover link An intelligent case-adjustment algorithm for the automated design of population-based quality auditing protocols