Rebeca Perez-Lainez, Ana Iglesias, Cesar de Pablo-Sanchez


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.


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Paper Citation

in Harvard Style

Perez-Lainez R., Iglesias A. and de Pablo-Sanchez C. (2009). ANONIMYTEXT: ANONIMIZATION OF UNSTRUCTURED DOCUMENTS . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009) ISBN 978-989-674-011-5, pages 284-287. DOI: 10.5220/0002297102840287

in Bibtex Style

author={Rebeca Perez-Lainez and Ana Iglesias and Cesar de Pablo-Sanchez},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)},

in EndNote Style

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)
SN - 978-989-674-011-5
AU - Perez-Lainez R.
AU - Iglesias A.
AU - de Pablo-Sanchez C.
PY - 2009
SP - 284
EP - 287
DO - 10.5220/0002297102840287