Leveraging Open-Source Large Language Models for Data Augmentation in Hospital Staff Surveys: Mixed Methods Study
The study demonstrates the value of data augmentation with open-source LLMs, highlights the importance of privacy and ethical considerations when using LLMs, and suggests future directions for research in this field.
Authors
- Carl Ehrett (ORCID: https://orcid.org/0000-0002-0711-0347)
- Dixizi Liu (ORCID: https://orcid.org/0009-0004-2422-5463)
- Sudeep Hegde (ORCID: https://orcid.org/0000-0001-9711-8459)
- Kwame Andre
- T. Wilson (ORCID: https://orcid.org/0009-0007-1711-6367)
Institutions
- Clemson University (US)
Publication Details
- Journal
- JMIR Medical Education
- Published
- 2024-08-15
- DOI
- https://doi.org/10.2196/51433
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.48