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评估-HRI:一个人工智能算法,用于测量出血的随机性
Jonathan D Stallings1, Srinivas Laxminarayan, Chenggang Yu
1US Army Institute of Surgical Research, Fort Sam Houston, Texas.
Shock (Augusta, Ga.)
|June 19, 2023
概括
一个人工智能算法,APPRAISE-出血风险指数 (HRI),可以分析生命体征,以识别出血高风险的创伤患者. 这种人工智能工具有助于医生优化战场伤亡者的分拣和治疗决策.
科学领域:
- 创伤护理的护理人员.
- 医学中的人工智能.
- 紧急医疗 紧急医疗
背景情况:
- 出血是战场死亡的主要原因.
- 创伤患者的有效分类对于生存至关重要.
- 目前的方法可能无法最佳地早期识别高风险出血患者.
研究的目的:
- 评估人工智能 (AI) 算法用于分析生命体征.
- 自动对创伤患者的出血风险进行分层.
- 为了开发APPRAISE-出血风险指数 (HRI) 算法.
主要方法:
- 开发了使用生命体征 (心率,血压) 的APPRAISE-出血风险指数 (HRI) 算法.
- 利用基于人工智能的线性回归模型对预处理的生命体征数据进行了利用.
- 在1659名创伤患者 (540小时的数据) 上训练并测试了算法.
主要成果:
- 评估-HRI算法将患者分为低 (HRI:I),平均 (HRI:II) 和高 (HRI:III) 的风险类别.
- 高风险患者 (HRI:III) 患出血的可能性是5.75倍.
- 与平均创伤人群相比,低风险患者 (HRI:I) 发生出血的可能性明显低.
结论:
- 评估-HRI算法提供了一种用于评估生命体征的新方法.
- 它可以提醒医务人员注意出血风险最高的伤员.
- 优化了在重症监护机构的分组,治疗和疏散的决策.
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