Modeling disagreement in automatic data labeling for semi-supervised learning in Clinical Natural Language Processing
Our conclusions highlight the utility of probabilistic models applied to "noisy" labels and that similar methods could provide utility for Natural Language Processing (NLP) based automated labeling tasks.
Authors
- Julia Ive (ORCID: https://orcid.org/0000-0002-3931-3392)
- Nabeel Seedat (ORCID: https://orcid.org/0000-0002-2134-6639)
- Liu Hongshu
Institutions
- Queen Mary University of London (GB)
- University of Cambridge (GB)
- Imperial College London (GB)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2024-10-02
- DOI
- https://doi.org/10.3389/frai.2024.1374162
- Citations
- 1
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.35