一个重症监护病房指挥中心的设计和实施,用于医疗数据融合
Wen-Sheng Feng1, Wei-Cheng Chen1, Jiun-Yi Lin1
1China Medical University Hospital (CMUH), Taichung 404327, Taiwan.
Sensors (Basel, Switzerland)
|June 27, 2024
概括
物体人工智能 (AIoT) 系统增强了医疗保健,特别是在重症监护室 (ICU). 这个AIoT数据融合系统显著改善了急性呼吸困扰综合征的诊断,并降低了死亡率.
科学领域:
- 医疗保健技术 技术 医疗保健 技术
- 人工智能的人工智能
- 物联网的物联网,就是物联网.
背景情况:
- 全球人口正在老龄化,预测显示到2050年,社会将会老龄化.
- 重症监护室 (ICU) 面临高医疗错误率,这是导致死亡的主要原因.
- 病人在ICU需要复杂的护理,增加医疗错误的脆弱性.
研究的目的:
- 为CMUH呼吸重症监护室 (RICU) 引入一个创新的AIoT支持的数据融合系统.
- 通过先进的数据管理来解决和减轻ICU中的医疗错误.
- 提高重症监护机构的患者结果和运营效率.
主要方法:
- 实施四层AIoT架构,用于实时和非实时的医疗数据管理.
- 使用三节点流集群 (Kafka) 进行不间断的RICU操作.
- 应用人工智能应用用于急性呼吸困扰综合征 (ARDS) 诊断.
主要成果:
- 该系统每年高效处理22TB的医疗数据,延迟最小 (1.72ms) 和带宽高 (65.66Mbps).
- 通过强大的流媒体集群,确保RICU的不间断运行.
- AIoT数据融合将ARDS诊断从52.2%提高到93.3%,并将死亡率从56.5%降低到39.5%.
结论:
- AIoT技术为改善ICU患者护理和运营效率提供了巨大的潜力.
- 开发的AIoT数据融合系统证明了减少医疗错误和死亡率的可行解决方案.
- 这种方法对于管理复杂的医疗数据和提高重症监护诊断准确度至关重要.
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