Performance of Retrieval-Augmented Generation Large Language Models in Guideline-Concordant Prostate-Specific Antigen Testing: Comparative Study With Junior Clinicians.

ABSTRACT:

Background

Prostate-specific antigen (PSA) testing remains the cornerstone of early prostate cancer detection. Society guidelines for prostate cancer screening via PSA testing serve to standardize patient care and are often used by trainees, junior staff, or generalist medical practitioners to guide medical decision-making. However, adherence to guidelines is a time-consuming and challenging task, and rates of inappropriate PSA testing are high. Retrieval-augmented generation (RAG) is a method to enhance the reliability of large language models (LLMs) by grounding responses in trusted external sources.

Objective

This study aimed to evaluate a RAG-enhanced LLM system, grounded in current European Association of Urology and American Urological Association guidelines, to assess

SUBMITTER: Tung JYM 

PROVIDER: S-EPMC12629621 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature