Linear accelerator (linac) downtime analysis assisted with a Large Language Model (LLM)
Our findings provide insights into the operational performance of LINACs over time, with implications for clinical budget management and maintenance scheduling. The data analysis methodology and LLM-based classification techniques developed in this study demonstrate an effective approach to analyzing historical maintenance records that could be applied at other institutions.
Authors
- Karl Farrey
- Joseph B. Schulz (ORCID: https://orcid.org/0000-0003-3005-6585)
- Emil Muresan
- Siyong Kim (ORCID: https://orcid.org/0000-0002-9173-7141)
- James J. Sohn (ORCID: https://orcid.org/0000-0001-7209-4104)
- Ethan Stolen (ORCID: https://orcid.org/0009-0003-7044-0263)
- Yeochan Youn (ORCID: https://orcid.org/0009-0003-3132-8009)
Institutions
- University of Wisconsin–Madison (US)
- Virginia Commonwealth University (US)
- University of Chicago (US)
Publication Details
- Journal
- Journal of Applied Clinical Medical Physics
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1002/acm2.70400
- Primary Topic
- Medical Coding and Health Information
- Type
- article
- Field-Weighted Citation Impact
- 0.00