AI in medical imaging: Practical vision-language model prompt engineering for radiologists
- Author(s)
- Yang, T; Stahlhoven, D; Ko, HS;
- Journal Title
- Current Problems in Diagnostic Radiology
- Publication Type
- Online publication before print
- Abstract
- The progressive advancement of generative artificial intelligence and in particular vision-language models (VLM) has led to its adoption and integration in radiology. Prompting, the process of providing instructional and contextual information (input) to the model, serves as a critical interaction influencing the quality and clinical usefulness of the output. This article provides an overview of the core prompting principles, provides practical examples of radiological application, and discusses limitations of VLMs relevant to clinical practice and education.
- Keywords
- Artificial intelligence; Education; Prompt engineering; Vision-language model
- Department(s)
- Cancer Imaging
- Publisher's Version
- https://doi.org/10.1067/j.cpradiol.2026.08.011
- Open Access at Publisher's Site
https://doi.org/10.1067/j.cpradiol.2026.08.011- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2026-10-12 05:40:54
Last Modified: 2026-10-12 05:41:16