ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2007.01030
6
18

NLNDE: The Neither-Language-Nor-Domain-Experts' Way of Spanish Medical Document De-Identification

2 July 2020
Lukas Lange
Heike Adel
Jannik Strötgen
ArXivPDFHTML
Abstract

Natural language processing has huge potential in the medical domain which recently led to a lot of research in this field. However, a prerequisite of secure processing of medical documents, e.g., patient notes and clinical trials, is the proper de-identification of privacy-sensitive information. In this paper, we describe our NLNDE system, with which we participated in the MEDDOCAN competition, the medical document anonymization task of IberLEF 2019. We address the task of detecting and classifying protected health information from Spanish data as a sequence-labeling problem and investigate different embedding methods for our neural network. Despite dealing in a non-standard language and domain setting, the NLNDE system achieves promising results in the competition.

View on arXiv
Comments on this paper