Abstract
Clinical NLP has an immense potential in contributing to how clinical practice will be revolutionized by the advent of large scale processing of clinical records. However, this potential has remained largely untapped due to slow progress primarily caused by strict data access policies for researchers. In this paper, we discuss the concern for privacy and the measures it entails. We also suggest sources of less sensitive data. Finally, we draw attention to biases that can compromise the validity of empirical research and lead to socially harmful applications.- Anthology ID:
- W17-1610
- Volume:
- Proceedings of the First ACL Workshop on Ethics in Natural Language Processing
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Dirk Hovy, Shannon Spruit, Margaret Mitchell, Emily M. Bender, Michael Strube, Hanna Wallach
- Venue:
- EthNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 80–87
- Language:
- URL:
- https://aclanthology.org/W17-1610
- DOI:
- 10.18653/v1/W17-1610
- Cite (ACL):
- Simon Šuster, Stéphan Tulkens, and Walter Daelemans. 2017. A Short Review of Ethical Challenges in Clinical Natural Language Processing. In Proceedings of the First ACL Workshop on Ethics in Natural Language Processing, pages 80–87, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- A Short Review of Ethical Challenges in Clinical Natural Language Processing (Šuster et al., EthNLP 2017)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/W17-1610.pdf