Artificial intelligence to advance acute and intensive care medicine.

IF 3.5 3区医学 Q1 CRITICAL CARE MEDICINE

Current Opinion in Critical Care Pub Date : 2024-06-01 Epub Date: 2024-03-22 DOI:10.1097/MCC.0000000000001150

Laurens A Biesheuvel, Dave A Dongelmans, Paul W G Elbers

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引用次数: 0

Abstract

Purpose of review: This review explores recent key advancements in artificial intelligence for acute and intensive care medicine. As artificial intelligence rapidly evolves, this review aims to elucidate its current applications, future possibilities, and the vital challenges that are associated with its integration into emergency medical dispatch, triage, medical consultation and ICUs.

Recent findings: The integration of artificial intelligence in emergency medical dispatch (EMD) facilitates swift and accurate assessment. In the emergency department (ED), artificial intelligence driven triage models leverage diverse patient data for improved outcome predictions, surpassing human performance in retrospective studies. Artificial intelligence can streamline medical documentation in the ED and enhances medical imaging interpretation. The introduction of large multimodal generative models showcases the future potential to process varied biomedical data for comprehensive decision support. In the ICU, artificial intelligence applications range from early warning systems to treatment suggestions.

Summary: Despite promising academic strides, widespread artificial intelligence adoption in acute and critical care is hindered by ethical, legal, technical, organizational, and validation challenges. Despite these obstacles, artificial intelligence's potential to streamline clinical workflows is evident. When these barriers are overcome, future advancements in artificial intelligence have the potential to transform the landscape of patient care for acute and intensive care medicine.

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人工智能推动急诊和重症监护医学的发展。

综述的目的：本综述探讨了人工智能在急诊和重症监护医学领域的最新主要进展。随着人工智能的快速发展，本综述旨在阐明人工智能目前的应用、未来的可能性，以及与人工智能融入急诊医疗调度、分诊、医疗咨询和重症监护室相关的重要挑战：人工智能与急诊医疗调度（EMD）的整合有助于快速、准确地进行评估。在急诊科（ED）中，人工智能驱动的分诊模型利用多样化的病人数据来改进结果预测，在回顾性研究中超过了人类的表现。人工智能可简化急诊室的医疗记录，并增强医学影像解读。大型多模态生成模型的引入展示了未来处理各种生物医学数据以提供全面决策支持的潜力。在重症监护室，人工智能的应用范围从早期预警系统到治疗建议。小结：尽管学术界取得了令人鼓舞的进展，但人工智能在急危重症护理领域的广泛应用仍受到伦理、法律、技术、组织和验证等方面挑战的阻碍。尽管存在这些障碍，但人工智能简化临床工作流程的潜力显而易见。只要克服这些障碍，人工智能的未来发展就有可能改变急重症医学患者护理的面貌。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Current Opinion in Critical Care 医学-危重病医学

CiteScore

5.90

自引率

3.00%

发文量

172

审稿时长

6-12 weeks

期刊介绍： Current Opinion in Critical Care delivers a broad-based perspective on the most recent and most exciting developments in critical care from across the world. Published bimonthly and featuring thirteen key topics – including the respiratory system, neuroscience, trauma and infectious diseases – the journal’s renowned team of guest editors ensure a balanced, expert assessment of the recently published literature in each respective field with insightful editorials and on-the-mark invited reviews.