LLMs in radiology through prompt engineering: Comment

10.1055/a-2264-5631

Dear Editor, we would like to share ideas on the publication “Improving the use of LLMs in radiology through prompt engineering: from precision prompts to zero-shot learning [1].” The goal of the study is to apply GPT4 to adjust the LLM ChatGPT to new tasks without requiring further training. Various prompting techniques are explained, such as sophisticated in-context techniques and precision prompts. Additionally covered is the importance of embeddings as a data representation method.

Publikationsverlauf

Eingereicht: 04. März 2024

Angenommen: 26. März 2024

Artikel online veröffentlicht:
14. Mai 2024

• References

• 1 Russe MF, Reisert M, Bamberg F. et al. Improving the use of LLMs in radiology through prompt engineering: from precision prompts to zero-shot learning. Fortschr Röntgenstr 2024;
• 2 Kleebayoon A, Wiwanitkit V. Artificial Intelligence, Chatbots, Plagiarism and Basic Honesty: Comment. Cell Mol Bioeng 2023; 16 (02) 173-174