Anonymisation of Swedish Clinical Data

Authors:
Dimitrios Kokkinakis;Anders Thurin
Affiliations:
Göteborg University, Department of Swedish Language, Språkdata, Sweden;Clinical Physiology, Sahlgrenska Univ. Hospital/Östra, Sweden
Venue:
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Year:
2007

Citing 2
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k-anonymity: a model for protecting privacy

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Named Entity recognition without gazetteers

EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics

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Abstract

There is a constantly growing demand for exchanging clinical and health-related information electronically. In the era of the Electronic Health Recordthe release of individual data for research, health care statistics, monitoring of new diagnostic tests and tracking disease outbreak alerts are some of the areas in which the protection of (patient) privacy has become an important concern. In this paper we present a system for automatic anonymisation of Swedish clinical free text, in the form of discharge letters, by applying generic named entity recognition technology.