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Cognitive Science Branch

The Cognitive Science Branch (CgSB) applies linguistic, statistical, and knowledge-based research and development in the investigation of techniques for improving access to biomedical information. Innovative CgSB research:

  • Builds and improves systems that extract biomedical information from free text
  • Seeks to determine the accessibility and understandability of health information
  • Develops systems to help users retrieve and integrate electronic biomedical information
  • Investigates all aspects of creating and disseminating digital library collections
  • Tests theories to enhance or improve current research and development activities

Additionally, branch members actively participate in developing and maintaining the Unified Medical Language System and collaborate with research staff to develop automated and semi-automated techniques for indexing biomedical literature


  • The Indexing Initiative (II) project investigates language-based and machine learning methods for the automatic selection of subject headings for use in both semi-automated and fully automated indexing environments at NLM. Its major goal is to facilitate the retrieval of biomedical information from textual databases such as MEDLINE.

  • BabelMeSH and PICO (Patient, Intervention, Comparison, and Outcome) Linguist are multi-language tools for searching MEDLINE/PubMed. Thirteen languages, including character-based languages, are supported. Recent enhancements include a query using more than one language and retrieving citations in more than one language.

  • Computational de-identification seeks to remove all of the identifiers in such narrative text in order to produce de-identified documents that can be used in research while protecting patient privacy.

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    The goal of this project, seen as a successor to DocView, is to develop a new collaborative tool to improve the delivery and exchange of medical and health information, especially information contained in very large files. MyDelivery is intended to enable biomedical researchers, administrators, librarians, physicians, patients, hospitals, and other health professionals to exchange medical information, regardless of the size of the electronic file or the number of files in which it resides.

  • LHNCBC's Lexical Systems Group develops and maintains the SPECIALIST lexicon and the tools that support and exploit it. The SPECIALIST Lexicon and NLP Tools are at the center of NLM's natural language research, providing a foundation for all our natural language processing efforts.

  • The LHNCBC Medical Ontology Research project encompasses basic research on biomedical terminologies and ontologies and their applications to natural language processing, clinical decision support, translational medicine, data integration and interoperability.

  • The Profiles in Science Web site showcases digital reproductions of items selected from the personal manuscript collections of prominent biomedical researchers, medical practitioners, and those fostering science and health. The Web site provides worldwide access to this unique biomedical information.

  • Pubmed for Handhelds image including handheld devices, a stethoscope, and an open book.

    PubMed for Handhelds research brings medical information to the point of care via devices like smartphones. This includes developing algorithms and public-domain tools for searching by text message (askMEDLINE and txt2MEDLINE), applying clinical filters (PICO) and viewing summary abstracts (The Bottom Line and Consensus Abstracts) in MEDLINE/PubMed, and evaluating the use of these tools in Clinical Decision Support.

  • Detail of several medication tablets

    RxNav is an interface to the RxNorm database, designed for displaying relations among drug entities. In addition to the browser, we created SOAP-based and RESTful application programming interfaces (APIs) enabling users to integrate RxNorm in their applications.

  • The Semantic Knowledge Representation project conducts basic research in symbolic natural language processing based on the UMLS knowledge sources. A core resource is the SemRep program, which extracts semantic predications from text. SemRep was originally developed for biomedical research.

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    Translational Science is a new field that develops new medical capabilities such as drugs, devices, and treatment options for patients, and then transitions those capabilities into medical practice as fast as is feasible. Steps in that transition can include clinical trials, clinical studies, and observational studies.