人工智能在患者呼吸器异步的管理:一个范围审查
Javier Muñoz1, Rocío Ruíz-Cacho1, Nerio José Fernández-Araujo1
1ICU. Hospital General Universitario Gregorio Marañón, Madrid, Spain.
Heart & lung : the journal of critical care
|May 24, 2025
概括
人工智能 (AI) 通过改进检测和预测,在管理患者呼吸器异步 (PVA) 方面表现有前途. 需要进一步的研究来验证人工智能工具在重症监护中广泛的临床使用.
科学领域:
- 关键护理医学 关键护理医学
- 生物医学工程 生物医学工程
- 医疗信息学 医疗信息学
背景情况:
- 患者呼吸器异步 (PVA) 在机械呼吸中很常见,导致肺损伤和死亡率增加等不良结果.
- 人工智能 (AI) 为检测,预测和管理PVA提供了潜在的解决方案.
- 目前对人工智能应用的理解和PVA管理中的证据差距需要全面审查.
研究的目的:
- 对管理PVA的基于AI的方法进行范围审查.
- 确定现有文献中的关键AI方法,研究趋势和局限性.
主要方法:
- 主要科学数据库 (PubMed,Embase等) 的系统搜索. 进行了.执行了.
- 数据提取包括研究目标,AI技术,患者组,绩效指标和临床结果.
- 研究结果按主题进行了综合,以绘制进展情况并确定研究缺口.
主要成果:
- 26项研究利用人工智能进行PVA检测,预测或优化.
- 包括CNN和LSTM在内的AI模型在检测异步事件方面实现了高精度 (87-99%) 和AUROC (>0.98).
- 人工智能在预测断奶成功和优化通风方面表现出潜力,但临床应用受到数据问题和缺乏可解释性的限制.
结论:
- 人工智能具有实时PVA检测,断奶预测和个性化通风的变革潜力.
- 重要的挑战包括需要多中心验证,标准化报告和临床疗效试验.
- 弥合人工智能模型和常规重症监护之间的差距需要解决这些局限性.
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