Evaluating Artificial Intelligence-Driven Responses to Acute Liver Failure Queries: A Comparative Analysis Across Accuracy, Clarity, and Relevance

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.