人工智能和机器学习在急性呼吸窘迫综合征管理方面:最近的进展
Songbei Li1,2, Ruiming Yue2, Sen Lu2
1School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Frontiers in medicine
|July 31, 2025
概括
人工智能 (AI) 和机器学习 (ML) 提供了管理急性呼吸困扰综合征 (ARDS) 的新方法. 这些技术可以改善早期预测,个性化治疗,并优化机械通风,以获得更好的患者结果.
科学领域:
- 关键护理医学 关键护理医学
- 生物医学信息学 生物医学信息学
- 人工智能的人工智能
背景情况:
- 由于高死亡率和患者变异性,急性呼吸困扰综合征 (ARDS) 在重症监护中构成了重大挑战.
- 目前对ARDS的支持性治疗由于患者异质性而具有有限的有效性.
研究的目的:
- 审查人工智能 (AI) 和机器学习 (ML) 在急性呼吸困扰综合征 (ARDS) 管理中的变革潜力.
- 探索各种AI/ML应用,以改善ARDS诊断,预后和治疗.
主要方法:
- 对ARDS中AI/ML应用的审查,包括预测,诊断,预后和治疗优化.
- 探索先进的人工智能方法,如图形神经网络,联合学习和大型语言模型 (LLM).
主要成果:
- 人工智能/ML可以通过使用多模式数据 (EHR,成像,波形) 增强早期预测和诊断.
- 人工智能驱动的预后评估和风险分层优于传统方法.
- 人工智能有助于识别ARDS亚型以进行个性化治疗,并优化机械通风和ECMO决策.
结论:
- 人工智能和机器学习为精准医学和ARDS的实时决策支持提供了前所未有的机会.
- 尽管存在数据和整合方面的挑战,但人工智能策略承诺在ARDS护理中改善患者的治疗结果.
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