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

ABSTRACT
Objective (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.

http://jamia.bmj.com/content/20/1/84.full.pdf html

Written by

Brian is a research scientist and educational technologist. He helped transform Pfizer’s Medical Education Group and previously served in educational leadership roles at HealthAnswers, Inc.; Acumentis, LLC.; Cephalon; and Wyeth. He taught graduate medical education programs at Arcadia University for 10 years. Dr. McGowan recently authored the book "#socialQI: Simple Solutions for Improving Your Healthcare" and has been invited to speak internationally on the subject of information flow, technology, and learning in healthcare.

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