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相关概念视频

Long-term Depression01:05

Long-term Depression

Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
Long-term Depression01:03

Long-term Depression

Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
Calcium Ion Concentration Mechanism
If over time, all...
Assessment of the Mouth01:26

Assessment of the Mouth

A thorough mouth assessment, including inspection and palpation of the lips, gums, tongue, tonsils, uvula, and pharynx, is crucial in detecting potential health issues. Diseases ranging from oral cancer to systemic conditions like diabetes could be identified early through careful oral examination. This article provides a detailed guide on conducting a comprehensive mouth assessment.
Mouth Inspection
The inspection begins with visually examining the mouth for symmetry, color, and size.

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相关实验视频

Updated: May 11, 2026

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors
08:32

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评估深度学习技术来识别抑郁症下值的舌头特征:一项前性观察性研究.

Bo Han1, Yue Chang2, Rui-Rui Tan3

  • 1Department of Rehabilitation, Daqing Longnan Hospital, Daqing, China.

Frontiers in psychiatry
|August 23, 2024
PubMed
概括

使用SEResNet101深度学习模型的舌头图像分析显示在诊断低值抑郁症方面具有很高的准确性. 这种方法也显示出对评估针治疗有效性的希望.

关键词:
这就是SEResNet101的意义.针治疗是一种治疗方法.相关性分析的相关性分析.深度学习是一种深度学习.在值以下的抑郁症.舌头图像特征 语言图像特征

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Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
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相关实验视频

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科学领域:

  • 综合医学是一个整体的医学.
  • 计算精神病学是一种计算精神病学.
  • 医学成像分析 医学成像分析

背景情况:

  • 低于值的抑郁症需要易于使用的诊断工具.
  • 非侵入性生物标志物对于早期检测至关重要.
  • 舌头图像分析提供了一个新的诊断途径.

研究的目的:

  • 为了评估舌头图像特征作为低值抑郁症的生物标志物.
  • 评估舌头特征与针治疗结果之间的相关性.
  • 应用先进的深度学习模型用于诊断和治疗评估.

主要方法:

  • 使用了五种深度学习模型 (DenseNet169,MobileNetV3Small,SeresNet101,SqueezeNet,VGG19_bn) 来进行舌头图像分析.
  • 使用准确度,精度,回忆和F1分数来评估模型性能.
  • 采用皮尔森的相关性,将模型预测与针治疗的成功联系起来.

主要成果:

  • 该SEResNet101模型表现出卓越的性能,准确率为98.5%,F1得分为0.97.
  • 在SEResNet101预测和针后症状改善之间观察到显著的正相关性 (r=0.72,p<0.001).
  • 舌头图像特征显示了作为可靠指标的潜力.

结论:

  • 通过舌头图像来诊断下值抑郁症,SeresNet101模型是准确可靠的.
  • 这种方法对监测针治疗疗效有希望.
  • 该研究提供了创新的方法,用于辅助诊断和治疗评估在下值抑郁症.