Large-scale evaluation of automated clinical note de-identification and its impact on information extraction.
(1) To evaluate a state-of-the-art natural language processing (NLP)-based approach to automatically de-identify a large set of diverse clinical notes. (2) To measure the impact of de-identification on the performance of information extraction algorithms on the de-identified documents.
Author(s): Deleger, Louise, Molnar, Katalin, Savova, Guergana, Xia, Fei, Lingren, Todd, Li, Qi, Marsolo, Keith, Jegga, Anil, Kaiser, Megan, Stoutenborough, Laura, Solti, Imre
DOI: 10.1136/amiajnl-2012-001012