HitzalMed: Anonymisation of Clinical Text in Spanish
Salvador Lima Lopez, Naiara Perez, Laura García-Sardiña, Montse Cuadros
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.- Anthology ID:
- 2020.lrec-1.870
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 7038–7043
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.870
- DOI:
- Cite (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.
- Cite (Informal):
- HitzalMed: Anonymisation of Clinical Text in Spanish (Lima Lopez et al., LREC 2020)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2020.lrec-1.870.pdf