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人工智能与急诊医学:机遇与挑战的平衡

Artificial Intelligence (AI) and Emergency Medicine: Balancing Opportunities and Challenges.

作者信息

Amiot Félix, Potier Benoit

机构信息

Emergency Department, Service d'Aide Médicale Urgente (SAMU50), Service Mobile d'Urgence et de Réanimation (SMUR), Saint-Lô Memorial Hospital, 715 rue Henri Dunant, Saint-Lô, 50000, France, 33 682640063.

出版信息

JMIR Med Inform. 2025 Aug 13;13:e70903. doi: 10.2196/70903.

Abstract

Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT, has rapidly evolved and is reshaping various fields, including clinical medicine. Emergency medicine stands to benefit from AI's capacity for high-volume data processing, workflow optimization, and clinical decision support. However, important challenges exist, ranging from model "hallucinations" and data bias to questions of interpretability, liability, and ethical use in high-stake environments. This updated viewpoint provides a structured overview of AI's current capabilities in emergency medicine, highlights real-world applications, and explores concerns regarding regulatory requirements, safety standards, and transparency (explainable AI). We discuss the potential risks and limitations of LLMs, including their performance in rare or atypical presentations common in the emergency department and potential biases that could disproportionately affect vulnerable populations. We also address the regulatory landscape, particularly the liability for AI-driven decisions, and emphasize the need for clear guidelines and human oversight. Ultimately, AI holds enormous promise for improving patient care and resource management in emergency medicine; however, ensuring safety, fairness, and accountability remains vital.

摘要

人工智能(AI),尤其是诸如ChatGPT之类的大语言模型(LLM),发展迅速,正在重塑包括临床医学在内的各个领域。急诊医学有望从人工智能处理大量数据、优化工作流程和提供临床决策支持的能力中受益。然而,也存在一些重大挑战,从模型“幻觉”和数据偏差到可解释性、责任以及在高风险环境中的道德使用等问题。这一更新的观点提供了人工智能在急诊医学中当前能力的结构化概述,突出了实际应用,并探讨了有关监管要求、安全标准和透明度(可解释人工智能)的问题。我们讨论了大语言模型的潜在风险和局限性,包括它们在急诊科常见的罕见或非典型病例中的表现,以及可能对弱势群体产生不成比例影响的潜在偏差。我们还探讨了监管环境,特别是人工智能驱动决策的责任,并强调了明确指导方针和人工监督的必要性。最终,人工智能在改善急诊医学中的患者护理和资源管理方面具有巨大潜力;然而,确保安全性、公平性和问责制仍然至关重要。

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