Text data is one of the major types of unstructured data generated in the real world i.e. the data that doesn’t have a predefined data model. It is already known that, the healthcare domain consists of the patient data in text type, which are available in the form of documents/reports. Especially, the hospital discharge summary document consists of the patient’s details, medications, and clinical procedures. The major issue here is, when these documents are subjected to text analytics operations like summarization, which is a process of extracting or describing the important aspects of document data as a summary, by Third Party or In House Data Scientist there is a possibility of patients’ privacy breach. To overcome the patient privacy breach, this research work has proposed a machine learning-based approach called sensitivity context aware privacy preserving text document summarization.


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    Titel :

    Sensitivity Context Aware Privacy Preserving Text Document Summarization


    Beteiligte:
    Shree, A N Ramya (Autor:in) / Kiran, P (Autor:in)


    Erscheinungsdatum :

    05.11.2020


    Format / Umfang :

    175071 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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