Using a Longformer Large Language Model for Segmenting Unstructured Cancer Pathology Reports

We present a fine-tuned Longformer model to isolate key sections from cancer pathology reports for downstream analyses. Our model performs segmentation with greater accuracy.

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Publication Details

Journal
JCO Clinical Cancer Informatics
Published
2025-03-01
DOI
https://doi.org/10.1200/cci-24-00143
Citations
1
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.81
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article

Using a Longformer Large Language Model for Segmenting Unstructured Cancer Pathology Reports

Gregory Arbour, Kaitlin Muzio, Karenina Nurmelita Malik, Raymond T. Ng et al.
1 citations
JCO Clinical Cancer Informatics
Biomedical Text Mining and Ontologies
0.81
article

Using a Longformer Large Language Model for Segmenting Unstructured Cancer Pathology Reports

Gregory Arbour, Kaitlin Muzio, Karenina Nurmelita Malik, Raymond T. Ng, Didier Fung
article en
1 citations

Abstract

We present a fine-tuned Longformer model to isolate key sections from cancer pathology reports for downstream analyses. Our model performs segmentation with greater accuracy.

JCO Clinical Cancer InformaticsVol. 9(9)
University of British Columbia (CA), University of Waterloo (CA)
Openalex Percentile: Top 30%
Biomedical Text Mining and Ontologies
0.81
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