Few shot chain-of-thought driven reasoning to prompt LLMs for open ended medical question answering

arXiv:2403.04890v1 Announce Type: new
Abstract: Large Language models (LLMs) have demonstrated significant potential in transforming healthcare by automating tasks such as clinical documentation, information retrieval, and decision support. In this aspect, carefully engineered prompts have emerged as a powerful tool for using LLMs for medical scenarios, e.g., patient clinical scenarios. In this paper, we propose a modified version of the MedQA-USMLE dataset, which is subjective, to mimic real-life clinical scenarios. We explore the Chain of Thought (CoT) reasoning based on …

abstract arxiv clinical cs.cl decision decision support documentation healthcare information language language models large language large language models llms medical prompt prompts question question answering reasoning retrieval support tasks thought tool type