Impact of De-Identification on Clinical Text Classification Using Traditional and Deep Learning Classifiers
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DOI: 10.3233/shti190228
Abstract: Clinical text de-identification enables collaborative research while protecting patient privacy and confidentiality; however, concerns persist about the reduction in the utility of the de-identified text for information extraction and machine learning tasks. In the context… read more here.
Keywords: clinical text; learning models; learning; impact identification ... See more keywords