清晰
医学
相关性(法律)
软件部署
人工智能
肝衰竭
数据科学
外科
计算机科学
生物化学
化学
政治学
法学
操作系统
作者
Sheza Malik,Lewis J. Frey,Jason Gutman,Asim Mushtaq,Fatima Warraich,Kamran Qureshi
标识
DOI:10.14309/ajg.0000000000003255
摘要
Recent advancements in Artificial Intelligence (AI), particularly through the deployment of Large Language Models (LLMs), have profoundly impacted healthcare. This study assesses five LLMs-ChatGPT 3.5, ChatGPT 4, BARD, CLAUDE, and COPILOT-on their response accuracy, clarity, and relevance to queries concerning acute liver failure (ALF). We subsequently compare these results with Chat GPT4 enhanced with Retrieval Augmented Generation (RAG) technology.
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