• Login
    View Item 
    •   DSpace@RPI Home
    • Tetherless World Constellation
    • Tetherless World Publications
    • View Item
    •   DSpace@RPI Home
    • Tetherless World Constellation
    • Tetherless World Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Knowledge Integration for Disease Characterization: A Breast Cancer Example

    Author
    Seneviratne, Oshani; Rashid, Sabbir; Chari, Shruthi; Bennett, Kristin; Hendler, Jim; McGuinness, Deborah
    Thumbnail
    Other Contributors
    Date Issued
    2018-07-20
    Subject
    Health Empowerment by Analytics, Learning, and Semantics (HEALS)
    Degree
    Terms of Use
    Metadata
    Show full item record
    URI
    https://arxiv.org/pdf/1807.07991; https://hdl.handle.net/20.500.13015/4448
    Abstract
    With the rapid advancements in cancer research, the information that is useful for characterizing disease, staging tumors, and creating treatment and survivorship plans has been changing at a pace that creates challenges when physicians try to remain current. One example involves increasing usage of biomarkers when characterizing the pathologic prognostic stage of a breast tumor. We present our semantic technology approach to support cancer characterization and demonstrate it in our end-to-end prototype system that collects the newest breast cancer staging criteria from authoritative oncology manuals to construct an ontology for breast cancer. Using a tool we developed that utilizes this ontology, physician-facing applications can be used to quickly stage a new patient to support identifying risks, treatment options, and monitoring plans based on authoritative and best practice guidelines. Physicians can also re-stage existing patients or patient populations, allowing them to find patients whose stage has changed in a given patient cohort. As new guidelines emerge, using our proposed mechanism, which is grounded by semantic technologies for ingesting new data from staging manuals, we have created an enriched cancer staging ontology that integrates relevant data from several sources with very little human intervention.;
    Department
    Relationships
    https://tw.rpi.edu/project/HEALS;
    Access
    Collections
    • Tetherless World Publications

    Browse

    All of DSpace@RPICommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    Login

    DSpace software copyright © 2002-2022  DuraSpace
    Contact Us | Send Feedback
    DSpace Express is a service operated by 
    Atmire NV