Large-scale evaluation of automated clinical note de-identification and its impact on information extraction

Abstract

NLP-based de-identification shows excellent performance that rivals the performance of human annotators. Furthermore, unlike manual de-identification, the automated approach scales up to millions of documents quickly and inexpensively.