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人在循环应用程序设计用于早期检测怀孕危险迹象

Melyana Nurul Widyawati¹, Ery Hadiyani Puji Astuti¹, Kurnianingsih²

¹Department of Midwifery, Poltekkes Kemenkes Semarang, Indonesia.

Belitung nursing journal

|July 31, 2023

概括

这项研究开发了一个使用Human-In-The-Loop设计的移动应用程序,以早期检测高风险怀孕. 该应用实现了92%的准确性,帮助医疗保健专业人员及时提供干预措施并改善孕产妇的结果.

科学领域:

孕产妇健康孕产妇健康
医疗信息学医疗信息学
公共卫生公共卫生

背景情况:

赋予孕妇信息是安全怀孕的关键.
识别怀孕预警信号可以预防严重的并发症和死亡率.
移动应用程序为孕妇的健康管理提供了宝贵的工具.

研究的目的:

使用Android应用程序应用一个HITL (Human-In-The-Loop) 设计.
为了使怀孕风险的早期检测.
为了减少孕产妇的发病率和死亡率.

主要方法:

从5324名孕妇 (2020-2021) 收集的数据.
在HITL移动应用程序中使用决策树算法.
纳入助产士审查以澄清数据和最终风险评估.

主要成果:

确定的风险因素:晚期的孕产妇年龄,高平价,低身高,短暂的妊娠间隔,低血红蛋白,低上臂周长 (UPC),HBsAg阳性,艾滋病毒,糖尿病 (DM),高血压和蛋白尿.
决策树实现了高准确度的92%±0.0351.1.
与个人分类器相比,HITL方法显示出更高的性能.

结论:

该HITL移动应用程序帮助医疗保健专业人员 (助产士,护士) 早期检测危险信号.
准确的高风险怀孕诊断是应用程序所促进的.
该应用程序支持在怀孕和分娩期间及时治疗和护理建议.

关键词:

在循环中的人类.早期检测早期检测机器学习是机器学习.助产士和助产士是什么意思移动应用程序移动应用程序护理护理护理怀孕危险的迹象怀孕危险的迹象

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