Anonimytext: Anonimization of unstructured documents

Abstract

The anonymization of unstructured texts is nowadays a task of great importance in several text mining applications. Medical records anonymization is needed both to preserve personal health information privacy and enable further data mining efforts. The described ANONYMITEXT system is designed to de-identify sensible data from unstructured documents. It has been applied to Spanish clinical notes to recognize sensible concepts that would need to be removed if notes are used beyond their original scope. The system combines several medical knowledge resources with semantic clinical notes induced dictionaries. An evaluation of the semi-automatic process has been carried on a subset of the clinical notes on the most frequent attributes.