AI in Patient Care: Evaluating Large Language Model Performance Against Evidence-Based Guidelines for Pulmonary Embolism
Key Points
Evaluate the performance of large language models (LLMs) in managing pulmonary embolism (PE) compared to evidence-based guidelines.
Assessment of LLMs in relation to PE management guidelines
Comparison of LLM performance across different domains of care
Analysis of guideline compliance in AI-generated responses
No single LLM consistently excelled across all evaluation domains
LLMs demonstrated potential in supporting PE management
Need for further development to improve clinical integration and adherence to guidelines
Abstract
AI-driven LLMs show promise in supporting PE management, though none consistently excel in all domains. Further development is needed to enhance clinical integration and guideline compliance.