Utility of a large language model for extraction of clinical findings from healthcare data following lung ablation: A feasibility study Journal Article
| Authors: | Geevarghese, R.; Solomon, S. B.; Alexander, E. S.; Marinelli, B.; Chatterjee, S.; Jain, P.; Cadley, J.; Hollingsworth, A.; Chatterjee, A.; Ziv, E. |
| Article Title: | Utility of a large language model for extraction of clinical findings from healthcare data following lung ablation: A feasibility study |
| Abstract: | To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radiology reports and clinic notes of 20 patients were extracted, up to 12 months after treatment. Utilizing an LLM (generative pretrained transformer 3.5 Turbo 16k), a zero-shot prompt strategy was employed to identify 4 key outcomes from relevant healthcare data: (a) recurrence at ablation site, (b) pneumothorax, (c) hemoptysis, and (d) hemothorax following ablation. This was validated with ground-truth labels obtained through manual chart review. Analysis of 104 radiology reports and 37 clinic notes was undertaken. The LLM output demonstrated high accuracy (85%–100%) across the 4 outcomes. An LLM approach appears to have utility in extraction of clinically relevant information from healthcare data. This method may be beneficial in facilitating data analysis for future interventional radiology studies. © 2024 SIR |
| Journal Title: | Journal of Vascular and Interventional Radiology |
| Volume: | 36 |
| Issue: | 4 |
| ISSN: | 1051-0443 |
| Publisher: | Elsevier Science, Inc. |
| Date Published: | 2025-04-01 |
| Start Page: | 704 |
| End Page: | 708 |
| Language: | English |
| DOI: | 10.1016/j.jvir.2024.11.029 |
| PUBMED: | 39662619 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PDF -- MSK corresponding author is Etay Ziv -- Source: Scopus |
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