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Using natural language processing to identify emergency department patients with incidental lung nodules requiring follow-up

Explosion
2025-01-17 1 min read

CT reports were annotated by MD raters using Prodigy software to develop a stepwise NLP “pipeline” that first excluded prior or known malignancy, determined the presence of a lung nodule, and then cat...

CT reports were annotated by MD raters using Prodigy software to develop a stepwise NLP “pipeline” that first excluded prior or known malignancy, determined the presence of a lung nodule, and then categorized any recommended follow-up. NLP was developed using a RoBERTa large language model on the spaCy platform.
Source: Explosion Word count: 265 words
Published on 2025-01-17 08:00