Abstract
Clinical data de-identification offers patient data privacy protection and eases reuse of clinical data. As an open-source solution to de-identify unstructured clinical text with high accuracy, CliniDeID applies an ensemble method combining deep and shallow machine learning with rule-based algorithms. It reached high recall and precision when recently evaluated with a selection of clinical text corpora.
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