Semi-Automatic De-identification of Hospital Discharge Summaries with Natural Language Processing: A Case-Study of Performance and Real-World Usability
Ioan Calapodescu, David Rozier, Svetlana Artemova, Jean‐Luc Bosson · 2017
Patient medical records represent a very rich and important source of information for clinical research. Still, this data cannot be used directly for research purposes, as these documents contain highly-sensitive personal information protected by the law. In this paper, we evaluate on real data the qualitative and quantitative impact of a semi-automated system (combining NLP processing, ML models and a dedicated UI) when used by human annotators for de-identifying French hospital discharge summaries.