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Article

Phenotyping Prostate Cancer in a National Health System Using Large Language Models.

JCO clinical cancer informatics - 1 Apr 2026

Dykstra Michael P, Tsao Phoebe A, Caram Megan E V, Nieto Josiah, Schipper Matthew, Stensland Kristian D, Elliott David, Rose Brent S, Bryant Alex K

Abstract excerpt

PURPOSE: Large language models (LLMs) may improve extraction of prognostic variables in prostate cancer from unstructured clinical text compared with traditional, rule-based natural language processing. METHODS: We used iterative prompt engineering with few-shot examples to develop LLM prompts for 30 phenotypes from prostate biopsy, radical prostatectomy (RP), and transurethral resection of the prostate (TURP)...

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PMID: 42284546
DOI: 10.1200/CCI-25-00314

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GPT

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