@inproceedings{lima-lopez-etal-2020-hitzalmed,
title = "{H}itzal{M}ed: Anonymisation of Clinical Text in {S}panish",
author = "Lima Lopez, Salvador and
Perez, Naiara and
Garc{\'\i}a-Sardi{\~n}a, Laura and
Cuadros, Montse",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.870",
pages = "7038--7043",
abstract = "HitzalMed is a web-framed tool that performs automatic detection of sensitive information in clinical texts using machine learning algorithms reported to be competitive for the task. Moreover, once sensitive information is detected, different anonymisation techniques are implemented that are configurable by the user {--}for instance, substitution, where sensitive items are replaced by same category text in an effort to generate a new document that looks as natural as the original one. The tool is able to get data from different document formats and outputs downloadable anonymised data. This paper presents the anonymisation and substitution technology and the demonstrator which is publicly available at \url{https://snlt.vicomtech.org/hitzalmed}.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>HitzalMed is a web-framed tool that performs automatic detection of sensitive information in clinical texts using machine learning algorithms reported to be competitive for the task. Moreover, once sensitive information is detected, different anonymisation techniques are implemented that are configurable by the user –for instance, substitution, where sensitive items are replaced by same category text in an effort to generate a new document that looks as natural as the original one. The tool is able to get data from different document formats and outputs downloadable anonymised data. This paper presents the anonymisation and substitution technology and the demonstrator which is publicly available at https://snlt.vicomtech.org/hitzalmed.</abstract>
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%0 Conference Proceedings
%T HitzalMed: Anonymisation of Clinical Text in Spanish
%A Lima Lopez, Salvador
%A Perez, Naiara
%A García-Sardiña, Laura
%A Cuadros, Montse
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F lima-lopez-etal-2020-hitzalmed
%X HitzalMed is a web-framed tool that performs automatic detection of sensitive information in clinical texts using machine learning algorithms reported to be competitive for the task. Moreover, once sensitive information is detected, different anonymisation techniques are implemented that are configurable by the user –for instance, substitution, where sensitive items are replaced by same category text in an effort to generate a new document that looks as natural as the original one. The tool is able to get data from different document formats and outputs downloadable anonymised data. This paper presents the anonymisation and substitution technology and the demonstrator which is publicly available at https://snlt.vicomtech.org/hitzalmed.
%U https://aclanthology.org/2020.lrec-1.870
%P 7038-7043
Markdown (Informal)
[HitzalMed: Anonymisation of Clinical Text in Spanish](https://aclanthology.org/2020.lrec-1.870) (Lima Lopez et al., LREC 2020)
ACL
- Salvador Lima Lopez, Naiara Perez, Laura García-Sardiña, and Montse Cuadros. 2020. HitzalMed: Anonymisation of Clinical Text in Spanish. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 7038–7043, Marseille, France. European Language Resources Association.