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走向智能,自动化交叉-AI模型,以解释在生理压力点上的血管封闭
Guy Avital1,2,3, Sofia I Hernandez Torres1, Zechariah J Knowlton1
1U.S. Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA.
一个人工智能算法使用超声波图像准确地检测血管堵塞,有助于控制结节出血. 这项技术可以指导压力应用用于挽救生命的干预.
科学领域:
- 医疗器械 医疗器械
- 人工智能的人工智能
- 紧急医疗 紧急医疗
背景情况:
- 流血,特别是十字路口出血,是可预防死亡的主要原因.
- 目前控制结节出血的方法往往是不够的.
- 控制出血的超声波指导在技术上要求很高.
研究的目的:
- 开发一种人工智能算法,用超声波来分类血管通透性或封闭性.
- 为了创建一个基本的步骤,自动化交叉路口门应用.
主要方法:
- 在超声波图像上训练神经网络模型,来自幻象和实体猪模型.
- 使用了带有和没有彩色多普勒叠加的图像.
- 开发了一种图像分类算法,以确定船只封闭状态.
主要成果:
- 人工智能模型在检测船舶封闭状态时达到93%以上的准确性.
- 该算法成功地用彩色多普勒测定了超声波图像中的透度或遮.
- 在定制幻影和实体猪模型中证明了可行性.
结论:
- 开发的AI方法可以指导和监测适当的血管封闭.
- 这种方法是朝着自动化交叉路口门系统迈出的重要一步.
- 进一步与自动启动集成可以增强紧急出血控制.
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