Aligning representations of anatomy using lexical and structural methods.
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OBJECTIVE: The objective of this experiment is to develop methods for aligning two representations of anatomy (the Foundational Model of Anatomy and GALEN) at the lexical and structural level. METHODS: The alignment consists of the following four steps: 1)acquiring terms, 2) identifying anchors (i.e., shared concepts) lexically, 3) acquiring explicit and implicit semantic relations, and 4) identifying anchors structurally. RESULTS: 2,353 anchors were identified by lexical methods, of which 91% were supported by structural evidence. No evidence was found for 7.5%of the anchors and 1.5% received negative evidence. DISCUSSION: The importance of taking advantage of implicit domain knowledge acquired through complementation,augmentation, and inference is discussed. (+info)
Proposed classification of cells in the Foundational Model of Anatomy.
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A logical and principled representation of cell types and their component parts could serve as a framework for correlating the various ontologies that are emerging in bioinformatics with a focus on cells and subcellular biological entities. In order to address this need we have extended the Foundational Model of Anatomy (FMA)1,2 from macroscopic to cellular and subcellular anatomical entities. The poster will provide a live demonstration of this implementation. (+info)
Efficient web-based navigation of the Foundational Model of Anatomy.
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The University of Washington's Foundational Model of Anatomy (FMA)1 is a complex, frame-based model composed of over 170,000 frames collectively specified by more than 1.4 million slot values. The Foundational Model Explorer (FME) was designed to provide simple and intuitive web access to this complex knowledge base. The Foundational Model Explorer (FME) (Figure 1) is built upon the Protege 2000 knowledge base access library [http://protege.stanford.edu/]. The FME application, associated libraries, and the FMA database all reside on remote servers. Users of the FME are not required to download, install, or set-up any of these components. The FME application, in response to a query, retrieves the appropriate information from the FMA, formats these data into html documents, and transmits them, via the Internet, back to the client where they can be viewed from any standard web browser (+info)
The evolving neuroanatomical component of the Foundational Model of Anatomy.
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In order to meet the need for an expressive ontology in neuroinformatics, we have integrated the extensive terminologies of NeuroNames and Terminologia Anatomica into the Foundational Model of Anatomy (FMA). We have enhanced the FMA to accommodate information unique to neuronal structures, such as axonal input/output relationships. (+info)
Mereotopological reasoning in anatomy.
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Applications in the field of computer assisted Surgery (e.g. navigation, robotics, simulation) need consistent formal models of anatomical part-whole relationship (mereology) and neighborhood (topology) to enable automated spatial reasoning. We investigated mereotopological theories in terms of their suitability for providing a logical background for such models. The so far results indicate a need for a more spatially motivated classification of anatomical structures to allow a consistent and logical-based mereotopological modelling. (+info)
Formative evaluation to guide early deployment of an online content management tool for medical curriculum.
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KM is a Web-accessible, comprehensive database that organizes course materials (at the level of full lectures, not just outlines or syllabi) from the Vanderbilt School of Medicine curriculum. KM uses natural language processing techniques to analyze educational documents for biomedical concepts. Lecture handouts and Microsoft PowerPoint presentations are indexed and available online for students, faculty and administrators to search for individual or interrelated concepts across the medical school curriculum. (+info)
Preserving and sharing examples of anatomical variation and developmental anomalies via photorealistic virtual reality.
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Computer graphics technology has made it possible to create photographic-quality virtual specimens from real anatomical material. One technique for doing this, QuickTime Virtual Reality (QTVR), results in virtual specimens that are easily shared on the Internet and displayed as standalone entities or incorporated into complex programs or Web sites. A compelling use of this technology is the sharing of rare specimens such as unusual variations, developmental anomalies or gross pathology. These types of specimens have traditionally been confined to anatomical museums, but could serve a much more useful existence as freely shared virtual specimens. An example presented here is a relatively rare developmental defect in the embryonic aortic arches that results in a right-sided aortic arch coursing posterior to the trachea and esophagus. In a time of ever increasing restraints on the practical side of anatomy education, an Internet-based library of human variation and other rare specimens would be a useful supplement to students' limited exposure to the human body. Since the discovery and preparation of specimens would be the rate-limiting step in producing such a collection, we propose the establishment of a center for virtual specimen creation and preservation through a cooperative effort by gross anatomists and pathologists in contributing the source material. This collection, a work in progress, is available at www.anatomy.wright.edu/qtvr. (+info)
A reference ontology for biomedical informatics: the Foundational Model of Anatomy.
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The Foundational Model of Anatomy (FMA), initially developed as an enhancement of the anatomical content of UMLS, is a domain ontology of the concepts and relationships that pertain to the structural organization of the human body. It encompasses the material objects from the molecular to the macroscopic levels that constitute the body and associates with them non-material entities (spaces, surfaces, lines, and points) required for describing structural relationships. The disciplined modeling approach employed for the development of the FMA relies on a set of declared principles, high level schemes, Aristotelian definitions and a frame-based authoring environment. We propose the FMA as a reference ontology in biomedical informatics for correlating different views of anatomy, aligning existing and emerging ontologies in bioinformatics ontologies and providing a structure-based template for representing biological functions. (+info)