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Communications Engineering Branch

The Communications Engineering Branch (CEB) is part of the Lister Hill National Center for Biomedical Communications, an intramural R&D division of the U.S. National Library of Medicine. Our mission is to conduct research and development directed toward mission-critical tasks at NLM and NIH, such as cancer research, document delivery, digital preservation, and automated ways of building resources such as MEDLINE.® All software products developed by our researchers are freely available.

Projects

  • chest x-ray image

    Research in machine learning and artificial intelligence (ML/AI) algorithms aims to improve computer-aided disease detection, accuracy and reliability. We develop novel computational solutions to analyze chest x-rays (CXR) and screen for cardiopulmonary diseases with a special interest in pulmonary TB in HIV+ population.

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    Multiple projects in this area continue to promote the development, enhancement, and adoption of clinical vocabulary standards. Inter-terminology mapping promotes the use of standard terminologies by creating maps to administrative terminologies, which allows re-use of encoded clinical data.

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    The consumer health question answering project was launched to support NLM customer services that receive about 90,000 requests a year from a world-wide pool of customers.

  • Discoveries from Clinical Data small image waveform

    Large database collections of clinical data -- from longitudinal research projects, electronic medical records, and health information exchanges -- provide opportunities to examine controversial findings from smaller scale clinical studies and to conduct retrospective epidemiological studies in areas that lack clinical trials.

  • Screenshot of the Boundary Marking Tool created for cancer research.

    The goal of our work in Biomedical Imaging is two-fold: One, to develop advanced imaging tools for biomedical research in partnership with the National Cancer Institute and other organizations. Secondly, to conduct research in Content Based Image Retrieval (CBIR) to index and retrieve medical images by image features (e.g., shape, color and texture), augmented by textual features as well.

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  • DocMorph is a web site that provides a useful information conversion service to the public while at the same time allowing NLM’s Communications Engineering Branch to investigate new image and information processing algorithms to find those that are fast, reliable and useful for the biomedical library community. It allows users on the Internet to upload via their web browsers scanned image files and other types of information for conversion to alternative formats. Some of the document conversion techniques offered by this server are not readily available elsewhere on the web.

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    System Screenshot

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    MyMorph screenshot

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  • This system automatically augments a patient's Electronic Health Record (EHR) with pertinent information from NLM resources. The software runs as background agents, both at a hospital and at NLM. The hospital uses our APIs to integrate the search setup and to display and store results in their existing EHR system.

  • malaria screener thumbnail

    To improve malaria diagnostics, we are developing a fully-automated system for parasite detection and counting in blood films in collaboration with NIH’s National Institute of Allergy and Infectious Diseases (NIAID) and Mahidol-Oxford University.

  • OpenI logo

    The Open-ism (pronounced “open eye”) experimental multimedia search engine retrieves and displays structured MEDLINE citations augmented by image-related text and concepts and linked to images based on image features.

  • lost person finder thumbnail

    The People Locator® (PL) is a Web system that enables family, friends and neighbors to locate or report missing people during a disaster event. Reporting and searching is done via a website and/or an app. In a disaster, this system can facilitate family reunification, help provide reassurance, enhance coordination with disaster-responding NGOs, and alleviate some of the workload on public-health personnel and other responders who interact with the community.

  • RIDeM provides access to key facts needed to support clinical decision making. The facts are extracted from biomedical literature and clinical text sources. The development of the Repository is guided by the Evidence Based Medicine (EBM) principles for finding and appraising information.