在出生和新生儿复苏过程中采集同意驱动的,半自动化的数据:来自NewbornTime研究的见解
Sara Brunner1, Anders Johannessen1, Jorge García-Torres2
1Laerdal Medical AS, Stavanger, Norway.
PLOS digital health
|September 8, 2025
概括
这项研究引入了一个自动化的AI视频系统,用于收集出生和新生儿复苏数据. 这项技术为质量改进和研究提供客观,一致和私有数据.
科学领域:
- 医疗技术 医疗技术 医学技术
- 人工智能的人工智能
- 新生儿护理 新生儿护理
背景情况:
- 手动收集出生和新生儿复苏的数据缺乏一致性,客观性和可扩展性.
- 现有的方法引发了隐私问题,可能不支持质量改进计划.
- 客观和一致的数据对于研究和改善新生儿护理至关重要.
研究的目的:
- 描述新生儿时间项目的自动化数据收集系统的实施.
- 开发一种人工智能系统,用于生成出生和复苏事件的准确时间表.
- 提供客观和一致的数据,以提高新生儿护理的质量和研究.
主要方法:
- 在分娩室使用热传感器,在复苏室使用热/可见光摄像头.
- 实施了一种数据收集流程,其中包括母亲的同意和医疗保健提供者的选择权.
- 设计系统以尽量减少对临床护理和提供者负担的干扰.
主要成果:
- 收集了1012个出生热视频和274个新生儿稳定/复苏的可见光视频.
- 数据收集发生在斯塔万格大学医院从2021年11月到2025年6月.
- 该系统有助于自动数据收集和人工智能视频处理.
结论:
- 自动化数据收集和人工智能视频处理可以增强新生儿护理的文档和质量改善.
- 这种方法为研究急性事件期间的治疗序列和时间提供了一致的客观数据.
- 该系统改善了参与者的隐私,并减少了数据捕获的负担.
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