Large Language Models to Help Appeal Denied Radiotherapy Services
When prompted appropriately, three commercially available LLMs drafted letters that physicians deemed would expedite appealing insurer denials of radiotherapy services. LLMs may decrease this task's clerical workload on providers. However, LLM performance worsened when fine-tuned with a task-specific, small training data set.
Authors
- Christopher Abraham (ORCID: https://orcid.org/0000-0002-6209-3316)
- Kendall Kiser (ORCID: https://orcid.org/0000-0001-7457-5534)
- Michael R. Waters (ORCID: https://orcid.org/0000-0001-5070-2244)
- Jocelyn Reckford
- Christopher Lundeberg
Institutions
- Washington University in St. Louis (US)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1200/cci.24.00129
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00