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Improving large language models accuracy for aortic stenosis treatment via Heart Team simulation: a prompt design analysis
3
Zitationen
9
Autoren
2025
Jahr
Abstract
Aims: Large language models (LLMs) have shown potential in clinical decision support, but the influence of prompt design on their performance, particularly in complex cardiology decision-making, is not well understood. Methods and results: < 0.001). Conclusion: Prompt design significantly impacts LLM performance in clinical decision-making for severe aortic stenosis. Tree-of-Thought prompting markedly improved accuracy and aligned recommendations with expert decisions, though LLMs tended toward conservative treatment approaches.
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