基于微波信号的深度神经网络早期诊断脑卒中和内出血

Ofir Tal, Shye Shapira
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引用次数: 1

摘要

介绍了一种紧凑的内出血自动诊断系统。利用微波传感和深度神经网络推理,该技术可以检测脑中风和腹部内出血。腹部内出血的检测灵敏度为92.9%。类似的程序导致对出血大于0.5ml的中风检测灵敏度为90%。结果建立了准确识别中风的能力,并使紧凑的自主系统能够在医院环境之外进行治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Early Diagnosis of Stroke and Internal Hemorrhage via Deep Neural Network Inference of Microwave Signals
A Compact automatic diagnostic system for internal hemorrhage is described. Utilizing microwave sensing and Deep Neural Network Inference, the technology detects brain stroke and internal abdominal hemorrhage. A sensitivity of 92.9% in detection of internal abdominal hemorrhage is demonstrated. A similar procedure leads to stroke detection with 90% sensitivity for hemorrhage larger than 0.5ml. Results establish the capability to accurately identify stroke and enable treatment with a compact autonomous system, outside the hospital environment.
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