Metastasis Extraction From Non-Small Cell Lung Cancer Clinical Notes Using Large Language Model-Based Classification: Retrospective Comparative Study.

Sweta Balaji¹, Kiersten Campbell¹, Rou-Zhen Chen², Daniel Smith³, Matthew A Reyna¹, Abeed Sarker¹, Joshua D Wallach², Ravi B Parikh⁴, Selen Bozkurt¹

¹Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.

²Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States.

³Department of IT and Research Informatics, Winship Cancer Institute, Atlanta, GA, United States.

⁴Department of Hematology and Medical Oncology, School of Medicine, Emory University, Atlanta, GA, United States.

PubMed DOI

Abstract

BACKGROUND: Identification of metastasis status in non-small cell lung cancer (NSCLC) is a critical part of understanding disease prognosis, treatment courses, trial eligibility, and population-level cancer surveillance. However, metastasis status is inconsistently recorded in structured cancer registry fields, since manual abstraction of clinical notes is often an error-prone process. This challe…

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