Prompt Engineering for Large Language Models: A Primer for Radiologists

Among artificial intelligence applications, large language models (LLMs) like ChatGPT have shown promising potential in streamlining workflows and facilitating research. This review article aims to provide basics and examples of prompt engineering in optimizing interactions with LLMs for radiologists, promoting precise, relevant, and useful LLM outputs.

Authors

Jeong Hyun Lee
Jinho Shin (ORCID: https://orcid.org/0000-0001-6706-6504)

Institutions

Samsung Medical Center (KR)

Publication Details

Journal: Korean Journal of Abdominal Radiology
Published: 2025-06-30
DOI: https://doi.org/10.52668/kjar.2024.00017
Primary Topic: Topic Modeling
Type: article
Field-Weighted Citation Impact: 0.00

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article

Prompt Engineering for Large Language Models: A Primer for Radiologists

Jeong Hyun Lee, Jinho Shin

Jun 30, 2025

Korean Journal of Abdominal Radiology

Topic Modeling

article

Prompt Engineering for Large Language Models: A Primer for Radiologists

Jeong Hyun Lee, Jinho Shin

June 30, 2025article en

Abstract

Korean Journal of Abdominal RadiologyVol. 8(1)

Samsung Medical Center (KR)

Openalex Percentile: Top 92%

Topic Modeling

DOI Open Access PDF OpenAlex

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Prompt Engineering for Large Language Models: A Primer for Radiologists — Jeong Hyun Lee, Jinho Shin · Korean Journal of Abdominal Radiology (2025) | TGRS Research Map | TGRS