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Updated: Jan 17, 2026

Author Spotlight: Utilizing Traditional Chinese Acupuncture of the Ear to Improve Sleep Disorders

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Published on: August 18, 2023

使用卷积神经网络识别耳部针点.

Junsuk Kim¹, Youngseok Kim¹, Da-Eun Yoon²

¹School of Information Convergence, Kwangwoon University, Seoul, Republic of Korea.

Integrative medicine research

|September 24, 2025

概括

人工智能 (AI) 准确识别耳部针点,显示出比传统方法更高的一致性. 这种人工智能模型提供了一种可靠的工具,用于提高针实践中的精度.

关键词:

人工智能的人工智能是人工智能.耳道中的针点.卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.位置位置位置预测预测预测

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Published on: August 18, 2023

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科学领域:

医疗针医学针是一种医疗的方法.
人工智能在医学中的应用
医学成像分析医学成像分析

背景情况:

准确的针点识别对于有效的针治疗至关重要.
人工智能 (AI) 为自动和精确的针点检测提供了潜力.
这项研究评估了人工智能模型用于耳部针点预测,与传统方法相比.

研究的目的:

评估人工智能模型在识别特定的耳部针点 (shenmen,肺,嘴) 中的准确性和一致性.
为了比较人工智能模型的性能与韩国传统医学从业者的针点安置.
探索AI在改善临床实践中的针点定位方面的潜力.

主要方法:

使用Mask R-CNN进行耳部区域隔离和CNN模型用于39个个人的耳部图像上的地标检测.
在大小调整的图像上训练CNN模型,以预测三个耳朵针点,将每个作为单独的坐标来处理可靠性.
使用核密度估计来分析针点分布并比较模型的一致性.

主要成果:

人工智能预测的针点中心点偏离从业者的位置不到3像素.
内核密度估计显示,与AI预测的针点分布更窄,表明更大的一致性.
与手动放置相比,人工智能模型在不同图像中的针点预测中表现出更高的一致性.

结论:

人工智能驱动的耳部针点识别显示了提高准确性和一致性的巨大潜力.
研究结果支持将人工智能整合为可靠的工具,以提高针的临床精度.
这项技术可以通过增强的定位精度来推进针的实践.