在劳动过程中基于人工智能的心脏图谱评估
Raoul Melaet1, Ivar R de Vries1, René D Kok2
1Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands; Nemo Healthcare BV, Veldhoven, the Netherlands.
European journal of obstetrics, gynecology, and reproductive biology
|February 10, 2024
概括
一种人工智能方法准确地解释心脏图谱 (CTG),以区分正常与病态的胎儿心率事件. 这种人工智能工具显示出有潜力帮助临床医生在分娩期间实时评估胎儿状况.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 胎儿监测 胎儿监测 胎儿监测
背景情况:
- 心脏图谱 (CTG) 对于在分娩期间评估胎儿健康至关重要.
- 解读CTG痕迹可能具有挑战性,需要专家临床判断.
- 需要客观的评估工具来支持产科医生做出决策.
研究的目的:
- 开发和评估一种基于人工智能的方法,用于解释心脏图形图像.
- 评估AI区分正常和病态胎儿心率事件的能力.
- 确定AI是否可以模仿或增强分娩室的临床决策.
主要方法:
- 开发了一种人工智能方法来预测胎儿对子宫活动的心率反应.
- 人工智能被训练在548个健康的胎儿的CTG数据上.
- 对87个胎儿的表现进行了评估,将AI预测与43个CTG的专家注释进行了比较.
主要成果:
- 在区分正常和病态CTG事件时,AI方法实现了0.96的曲线下的面积 (AUC).
- 人工智能的表现与三个经验丰富的妇科医生之间的协议非常相匹配.
- 人工智能展示了近乎实时解释的能力.
结论:
- 开发的AI方法有效地区分正常的CTG事件和病态的CTG事件.
- 人工智能显示出强大的潜力,作为临床医生评估胎儿状况的支持工具.
- 这项技术可以提高产后胎儿监测的准确性和效率.
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