Optimizing Large Language Models for Automated Protocoling of Abdominal and Pelvic CT Scans: The Power of Context

Radiology 2026

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Authors: Bryan Buckley, Adriano B. Dias, Yangqing Deng, Heidi Schmidt, Ania Z. Kielar, Satheesh Krishna, Rajesh Bhayana
DOI: 10.1148/radiol.252105
Cited by: 7
References: 27

Abstract

= .30). Conclusion For protocoling abdominal and pelvic CT scans, the LLM, GPT-4o, selected optimal protocols more frequently than radiologists when optimized with detailed prompting, and fine-tuning of the model did not further improve performance. © RSNA, 2026

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Machine Learning in Healthcare Topic Modeling

Publication details

Journal / source
Radiology
Publisher
Radiological Society of North America (RSNA)
Volume
318
Issue
1
Pages
e252105–e252105
Publication date
1 January 2026
Language
EN