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PubMed2005

Qualitative assessment of the International Classification of Functioning, Disability, and Health with respect to the desiderata for controlled medical vocabularies.

BACKGROUND: The International Classification of Functioning, Disability, and Health (ICF), a classification system published in 2001 by the World Health Organization (WHO), provides a common language and framework for describing functional status information (FSI) in health records. METHODS: Informed by ongoing research in coding FSI in patient records, this paper qualitatively assesses the ICF framework with respect to the desiderata for controlled medical vocabularies, an enumerated a list of desirable qualities for controlled medical vocabularies proposed by Cimino [J.J. Cimino, Desiderata for controlled medical vocabularies in the twenty-first century, Meth. Inform. Med. 37 (1998) 394-403]. RESULTS: The ICF satisfies 5 of the 12 desiderata. Five points were not satisfied and two points could not be evaluated. CONCLUSION: The ICF is a rich source of relevant terms, concepts, and relationships, but it was not developed in consideration of requirements for formal terminologies. Therefore, it could serve as a base from which to develop a formal terminology of functioning and disability. This assessment is a key next step in the development of the ICF as a sensitive, universal measure of functional status.

Decision Support Techniques↗

PubMedDate not supplied

Standards for nursing terminology.

Terminology work in nursing has given rise to an increasing number of nursing terminologies. These generally take the form of controlled vocabularies. Because of the limitations of the controlled vocabulary approach, individual terminologies tend to be tuned to meet the specific needs of their intended users. Differences between terminologies are now a significant barrier to the comparison and interchange of health information. To agree on a single, multipurpose terminology would be problematic. However, several options for resolving unnecessary differences between nursing terminologies are currently being explored by international standards bodies and other groups, such as the U.S. Nursing Vocabulary Summit. One such option is the use of a terminology model to facilitate evolution toward a more coherent range of terminologies. The authors describe the motivation behind the development of a standard for nursing terminologies. They explain how a terminology model might form the basis for such a standard through a description of the approach taken by CEN TC251 (the Health Informatics Technical Committee of the European Committee for Standardization). They also discuss possible limitations of standardization.

Nursing↗

PubMed2005

Ontology integration: experience with medical terminologies.

To build a common controlled vocabulary is a formidable challenge in medical informatics. Due to vast scale and multiplicity in interpretation of medical data, it is natural to face overlapping terminologies in the process of practicing medical informatics [A. Rector, Clinical terminology: why is it so hard? Methods Inf. Med. 38 (1999) 239-252]. A major concern lies in the integration of seemingly overlapping terminologies in the medical domain and this issue has not been well addressed. In this paper, we describe a novel approach for medical ontology integration that relies on the theory of Algorithmic Semantic Refinement we previously developed. Our approach simplifies the task of matching pairs of corresponding concepts derived from a pair of ontologies, which is vital to terminology mapping. A formal theory and algorithm for our approach have been devised and the application of this method to two medical terminologies has been developed. The result of our work is an integrated medical terminology and a methodology and implementation ready to use for other ontology integration tasks.

Algorithms↗

PubMed2005

UMLF: a unified medical lexicon for French.

Medical Informatics has a constant need for basic medical language processing tasks, e.g. for coding into controlled vocabularies, free text indexing and information retrieval. Most of these tasks involve term matching and rely on lexical resources: lists of words with attached information, including inflected forms and derived words, etc. Such resources are publicly available for the English language with the UMLS Specialist Lexicon, but not in other languages. For the French language, several teams have worked on the subject and built local lexical resources. The goal of the present work is to pool and unify these resources and to add extensively to them by exploiting medical terminologies and corpora, resulting in a unified medical lexicon for French (UMLF). This paper exposes the issues raised by such an objective, describes the methods on which the project relies and illustrates them with experimental results.

Abstracting and Indexing↗

PubMed2002

Structured documentation.

Structured documentation is a concept-oriented method of capturing clinical information that can be shared readily through automated systems. Standards are evolving for controlled vocabularies that are applicable to various aspects of clinical medicine. Vocabulary expressiveness and the significant preparatory work needed to use structured terms are hindrances to the rapid acceptance of these tools; however, the benefits of increased efficiencies, data sharing, and automated triggers may outweigh the cost of these hindrances. Understanding the basic principles of structured documentation and defining the use of the structured data within a practice allows an organization to select a tool that most closely fits its needs.

Documentation↗

PubMed2000

Expanding DIOGENE with a clinical information system based on a new hospital-wide clinical findings dictionary.

The DIOGENE hospital information system has been expanded with a centralized and integrated patient clinical database recording structured patient data. The objective is to provide a standardized framework for the building of future clinical databases and for the integration of existing heterogeneous ones. The combined 'across time view' and 'across departments view' generated from the integrated clinical data will enable an evolutionary view of the patient state, both across time and across medical specialties. For this purpose and to permit the communication and exchange of data, a new controlled vocabulary for representing clinical data has been created. The construction of this vocabulary is based on the international ICD classification, already being used in DIOGENE for encoding patient diagnosis and procedures. A new extension of the ICD is proposed for medical information that goes beyond diagnosis and procedures encoding. The building of a common clinical findings dictionary, recording the definition of clinical entities, is based on this newly developed clinical vocabulary. This process is incremental, manual and substantial.

Decision Support Systems, Clinical↗

PubMed2003

A formal representation for messages containing compositional expressions.

Clinically useful controlled vocabularies should represent healthcare concepts completely and with high reliability. Anticipating and pre-coordinating all possible expressions (e.g. 'fracture of the left femur' and 'fracture of the right femur') is not feasible. Variation in practice styles, requirements for the granularity of content, the exponential growth of terminology size, and increased cost of maintaining pre-coordinated terminologies lead us to conclude that no enumerated terminology can ever be truly comprehensive. Compositional terminologies are one potential solution to the problem of content completeness, but carry a risk of generating expressions whose equivalency cannot be easily determined. In order for post-coordinated expressions to be comparable, a sufficiently detailed formal mechanism for information representation is necessary. Comparable data for post-coordinated expressions requires normalization of both the contents and the semantics of the contents of the terminology with the information captured in post-coordinated expressions. In addition, comparable data requires a storage and messaging paradigm robust enough to faithfully represent the information contained within arbitrarily complex compositional expressions. We present a formalism for storing, and sending messages containing compositional expressions using a large-scale reference terminology. It is our intent that this formalism be used to algorithmically determine whether or not messages contain comparable data. In addition, we advocate transmitting the upward transitive closure of subsumption of all concepts, to improve comparability of data and to decrease reliance on locally stored versions of the underlying reference terminology.

Abstracting and Indexing↗

PubMed2006

The work of the Human Proteome Organisation's Proteomics Standards Initiative (HUPO PSI).

This article describes the origins, working practices and various development projects of the HUman Proteome Organisation's Proteomics Standards Initiative (HUPO PSI), specifically, our work on reporting requirements, data exchange formats and controlled vocabulary terms. We also offer our view of the two functional genomics projects in which the PSI plays a role (FuGE and FuGO), discussing their impact on our process and laying out the benefits we see as accruing, both to the PSI and to biomedical science as a whole as a result of their widespread acceptance.

Humans↗

PubMed2003

SEMEDA: ontology based semantic integration of biological databases.

MOTIVATION: Many molecular biological databases are implemented on relational Database Management Systems, which provide standard interfaces like JDBC and ODBC for data and metadata exchange. By using these interfaces, many technical problems of database integration vanish and issues related to semantics remain, e.g. the use of different terms for the same things, different names for equivalent database attributes and missing links between relevant entries in different databases. RESULTS: In this publication, principles and methods that were used to implement SEMEDA (Semantic Meta Database) are described. Database owners can use SEMEDA to provide semantically integrated access to their databases as well as to collaboratively edit and maintain ontologies and controlled vocabularies. Biologists can use SEMEDA to query the integrated databases in real time without having to know the structure or any technical details of the underlying databases. AVAILABILITY: SEMEDA is available at http://www-bm.ipk-gatersleben.de/semeda/. Database providers who intend to grant access to their databases via SEMEDA are encouraged to contact the authors.

Computational Biology↗

PubMed2004

Genome Properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics.

MOTIVATION: The presence or absence of metabolic pathways and structures provide a context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics. RESULTS: We have created a Genome Properties system to present key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny and computational analyses. The results of searches using hidden Markov models allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports and other forms of evidence. Genome Properties system was applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties. AVAILABILITY: Genome Properties can be found at http://www.tigr.org/Genome_Properties SUPPLEMENTARY INFORMATION: http://www.tigr.org/tigr-scripts/CMR2/genome_properties_references.spl.

Chromosome Mapping↗

PubMed2006

Automatic extension of Gene Ontology with flexible identification of candidate terms.

MOTIVATION: Gene Ontology (GO) has been manually developed to provide a controlled vocabulary for gene product attributes. It continues to evolve with new concepts that are compiled mostly from existing concepts in a compositional way. If we consider the relatively slow growth rate of GO in the face of the fast accumulation of the biological data, it is much desirable to provide an automatic means for predicting new concepts from the existing ones. RESULTS: We present a novel method that predicts more detailed concepts by utilizing syntactic relations among the existing concepts. We propose a validation measure for the automatically predicted concepts by matching the concepts to biomedical articles. We also suggest how to find a suitable direction for the extension of a constantly growing ontology such as GO. AVAILABILITY: http://autogo.biopathway.org SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Algorithms↗

PubMed2002

Annotating the human proteome: the Human Proteome Survey Database (HumanPSD) and an in-depth target database for G protein-coupled receptors (GPCR-PD) from Incyte Genomics.

The Proteome Division of Incyte Genomics has released new volumes to the BioKnowledge Library to add human, mouse and rat protein information to its rich collection of model organism Proteome Databases. The Human Proteome Survey Database (HumanPSD) compiles the fundamental properties of more than 25 000 characterized mammalian proteins. HumanPSD includes clear, concise and current protein descriptions (Title Lines), the protein sequence, calculated physical properties, precomputed BLAST alignments, controlled-vocabulary protein properties and Gene Ontology terms, and a list of published references. Each report also contains expression data, Pfam domain information and an associated Mouse Mutant Phenotype section describing behavioral, physiological and cellular phenotypes for over 1500 mouse mutant phenotypes. GPCR-PD contains more than 3200 Protein Reports from the three mammalian species for G protein-coupled receptors, their protein ligands, associated G-proteins and their downstream signaling proteins. In addition to the features described above, each GPCR-PD Protein Report displays annotations of experimental findings from over 10 000 publications. These databases provide important new volumes of Proteome's BioKnowledge Library (http://www.incyte.com), integrating protein information from model organisms with the human proteome.

Amino Acid Sequence↗

PubMed2004

Pathbase: a database of mutant mouse pathology.

Pathbase is a database that stores images of the abnormal histology associated with spontaneous and induced mutations of both embryonic and adult mice including those produced by transgenesis, targeted mutagenesis and chemical mutagenesis. Images of normal mouse histology and strain-dependent background lesions are also available. The database and the images are publicly accessible (http://www.pathbase.net) and linked by anatomical site, gene and other identifiers to relevant databases; there are also facilities for public comment and record annotation. The database is structured around a novel ontology of mouse disorders (MPATH) and provides high-resolution downloadable images of normal and diseased tissues that are searchable through orthogonal ontologies for pathology, developmental stage, anatomy and gene attributes (GO terms), together with controlled vocabularies for type of genetic manipulation or mutation, genotype and free text annotation for mouse strain and additional attributes. The database is actively curated and data records assessed by pathologists in the Pathbase Consortium before publication. The database interface is designed to have optimal browser and platform compatibility and to interact directly with other web-based mouse genetic resources.

Animals↗

PubMed2006

BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems.

BioModels Database (http://www.ebi.ac.uk/biomodels/), part of the international initiative BioModels.net, provides access to published, peer-reviewed, quantitative models of biochemical and cellular systems. Each model is carefully curated to verify that it corresponds to the reference publication and gives the proper numerical results. Curators also annotate the components of the models with terms from controlled vocabularies and links to other relevant data resources. This allows the users to search accurately for the models they need. The models can currently be retrieved in the SBML format, and import/export facilities are being developed to extend the spectrum of formats supported by the resource.

Biochemical Phenomena↗

PubMed2001

Dynamic publication model for neurophysiology databases.

We have implemented a pair of database projects, one serving cortical electrophysiology and the other invertebrate neurones and recordings. The design for each combines aspects of two proven schemes for information interchange. The journal article metaphor determined the type, scope, organization and quantity of data to comprise each submission. Sequence databases encouraged intuitive tools for data viewing, capture, and direct submission by authors. Neurophysiology required transcending these models with new datatypes. Time-series, histogram and bivariate datatypes, including illustration-like wrappers, were selected by their utility to the community of investigators. As interpretation of neurophysiological recordings depends on context supplied by metadata attributes, searches are via visual interfaces to sets of controlled-vocabulary metadata trees. Neurones, for example, can be specified by metadata describing functional and anatomical characteristics. Permanence is advanced by data model and data formats largely independent of contemporary technology or implementation, including Java and the XML standard. All user tools, including dynamic data viewers that serve as a virtual oscilloscope, are Java-based, free, multiplatform, and distributed by our application servers to any contemporary networked computer. Copyright is retained by submitters; viewer displays are dynamic and do not violate copyright of related journal figures. Panels of neurophysiologists view and test schemas and tools, enhancing community support.

Animals↗

PubMedDate not supplied

Auditing the Unified Medical Language System with semantic methods.

OBJECTIVE: The National Library of Medicine's (NLM) Unified Medical Language System (UMLS) includes a Metathesaurus (Meta), which is a compilation of medical terms drawn from over 30 controlled vocabularies, and a Semantic Net, which contains the semantic types used to categorize Meta concepts and the semantic relations to connect them. Meta has been constructed through lexical matching techniques and human review. The purpose of this study was to audit the Meta using semantic techniques to identify possible inconsistencies. METHODS: Five different techniques were applied: (1) detection of ambiguity in Meta concepts with two or more semantic types, (2) detection of interchangeable keyword synonyms, (3) detection of redundant pairs of Meta concepts (using lexical matching combined with keyword synonyms), (4) detection of inconsistent parent-child relationships in Meta (based on the semantic type information), and (5) discovery of pairs of semantic types for which relations could be added to the Semantic Net, based on "other" relationships between Meta concepts. RESULTS: Of 57,592 concepts with multiple semantic types, 1817 (3.2%) were judged to be ambiguous. Keyword analysis showed 7121 pairs of interchangeable words. Using the keyword pairs, 5031 pairs of potentially redundant concepts were suggested, of which 3274 (65.1%) were judged to actually be redundant. Review of the 100,586 parent-child relationships revealed 544 (0.54%) that were incorrect. Review of the 219,664 "Other" relationships suggested 1299 places in the Semantic Net where relations between pairs of semantic types could be added. CONCLUSION: Semantic techniques, alone or in combination, can be used to audit the UMLS to detect inconsistencies that are not detectable through lexical techniques alone. Use of these methods to augment the UMLS maintenance process will lead to improvement in the UMLS.

Algorithms↗

PubMedDate not supplied

Medical subject headings used to search the biomedical literature.

The National Library of Medicine's MEDLINE (MEDLARS Online) database was the first database to be searched nationwide via value-added telecommunication networks. Now available on the World Wide Web free of charge from the National Library of Medicine and from many other sources, it is the world's most heavily used medical database. MEDLINE is unique in that each reference to the medical literature is indexed under a controlled vocabulary called Medical Subject Headings (MeSH). These headings are the keys that unlock the medical literature. MeSH multiplies the usefulness of the MEDLINE database and makes it possible to search the medical literature as we do today. This paper commemorates the 40th anniversary of the introduction of MeSH and salutes some of the farsighted persons who conceived and developed the MEDLINE database.

Abstracting and Indexing↗

PubMed2004

Bioie: retargetable information extraction and ontological annotation of biological interactions from the literature.

The need for extracting general biological interactions of arbitrary types from the rapidly growing volume of the biomedical literature is drawing increased attention, while the need for this much diversity also requires both a robust treatment of complex linguistic phenomena and a method to consistently characterize the results. We present a biomedical information extraction system, BioIE, to address both of these needs by utilizing a full-fledged English grammar formalism, or a combinatory categorial grammar, and by annotating the results with the terms of Gene Ontology, which provides a common and controlled vocabulary. BioIE deals with complex linguistic phenomena such as coordination, relative structures, acronyms, appositive structures, and anaphoric expressions. In order to deal with real-world syntactic variations of ontological terms, BioIE utilizes the syntactic dependencies between words in sentences as well, based on the observation that the component words in an ontological term usually appear in a sentence with known patterns of syntactic dependencies.

Abstracting and Indexing↗