开发一种人工智能辅助系统,用于在婴儿和新生儿中使用视频喉镜进行气管管管道输入
Hiroki Nakamura1, Kouki Fukuda2, Takahiko Asano2
1Pain Center, Kouseikai Takai Hospital, Nara, Japan; NCD Epidemiology Research Center, Shiga University of Medical Science, Shiga, Japan.
一个人工智能 (AI) 模型有助于在视频喉镜检查期间识别婴儿喉,提高输管安全. 然而,需要进一步细化,以解决食道误认问题.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 儿科麻醉学 儿科麻醉学
背景情况:
- 在婴儿中通过视频喉腔镜识别喉带来了挑战.
- 准确的可视化对于安全的气管管道输入至关重要.
研究的目的:
- 开发一种人工智能辅助的模型,用于识别婴儿喉,声带和状腺区域.
- 为了提高新生儿和婴儿气管输管的安全性.
主要方法:
- 从653个视频中使用了1197张图像进行培训和验证.
- 使用YOLOv8n架构开发了一个AI模型.
- 在63个视频中的399张图像上测试了模型.
主要成果:
- 人工智能模型实现了0.74的灵敏度,0.99的特异性和0.91的AUC.
- 在无障碍的视图中成功识别了声带和状腺.
- 由于障碍,观察到食道错误识别和错过喉检测.
结论:
- 人工智能模型在视频喉镜检查过程中有效地识别了关键的喉结构.
- 有潜力提高婴儿和新生儿气管输管的安全性.
- 食道错误识别需要进一步调查和模型改进.
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