Prompting is All You Need: How to Make LLMs More Helpful for Clinical Decision Support
Structured prompting substantially enhances LLM performance for acute stroke thrombolysis CDS. Notably, some models, including the proprietary GPT-4o and o3, and the open-source reasoning model r1-1776, achieved excellent safety and adherence with structured prompts. For clinical deployment of any LLM, structured prompts are crucial, and vigilant human oversight remains essential.
Authors
- Braydon Dymm (ORCID: https://orcid.org/0000-0002-3598-6223)
- Daniel M. Goldenholz (ORCID: https://orcid.org/0000-0002-8370-2758)
Institutions
- Charleston Area Medical Center (US)
- Harvard University (US)
- Hadassah Medical Center (IL)
Publication Details
- Journal
- medRxiv
- Published
- 2026-02-22
- DOI
- https://doi.org/10.64898/2026.02.12.26346005
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00