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Updated: Jan 13, 2026

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PPG-Net 4:基于深度学习的方法,使用非侵入式双光电显微镜 (PPG) 信号对血流进行分类

Manisha Samant1, Utkarsha Pacharaney1

  • 1Datta Meghe Institute of Higher Education & Research (DMIHER), Wardha 442004, Maharashtra, India.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
概括

这项研究介绍了PPG-Net 4,一种使用双光多聚光学 (PPG) 信号进行非侵入性血液流动模式分类的深度学习模型. 它为早期心血管疾病的检测和监测提供了一个有前途的工具.

关键词:
人民防卫品的信号血液流的分类,血液流的分类.深度学习是一种深度学习.机器学习是机器学习.非侵入性诊断是一种非侵入性诊断.摄影复合体学 摄影复合体学 摄影复合体学

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