IMIA Academic Representative:
Dr. Mark A. Musen
Stanford Medicine Professor of Biomedical Informatics Research, Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
The Stanford Center for Biomedical Informatics Research (BMIR) is an interdisciplinary academic and research group within the Department of Medicine in the Stanford University School of Medicine.
BMIR is home to scientists developing cutting-edge ways to acquire, represent, process, and manage knowledge and data related to health, health care, and the biomedical sciences. Our faculty, students, and researchers are committed to ensuring the biomedical community is properly equipped for the information age by creating and validating models of how knowledge and data are used in biomedicine.
BMIR scientists and researchers work toward providing the structure necessary to handle the ever-increasing amounts of data in the revolution of health care, and to support information-intensive problems in all areas of biomedicine by studying and creating novel computational, statistical, organizational, and decision-making software, repositories, and other useful products.
In the 1970s, BMIR scientists performed path-defining work in knowledge representation and intelligent systems. In the 1980s, much of the work in large-scale Bayesian reasoning in biomedicine emerged from our laboratory. In the 1990s, we pioneered work in biomedical ontology and initiated the Protégé resource, the most widely used open-source ontology-development system in the world. Our emphasis on declarative representation of biomedical knowledge and on automated reasoning continues to this day, as BMIR is the home of the National Center for Biomedical Ontology, one of the seven National Centers for Biomedical Computing founded in the United States under the NIH Roadmap.
Primary areas of research include:
– Representation, management, and dissemination of biomedical knowledge in machine-processable form
– Advancement of Semantic Web technologies and model-driven architectures
– Knowledge discovery from high-throughput data, leading to advances in our understanding of diabetes, obesity, and other diseases with complex inheritance patterns
– Knowledge-based support for biomedical data integration, decision making for translational research, guideline-directed care, and public health surveillance
For more information on BMIR, please see our Web site at http://bmir.stanford.edu