一个系统的计算机辅助针点定位的系统审查
Zhenwei Zhai1, Zihao Wang2, Lin Xu3
1School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
iScience
|November 10, 2025
概括
使用人工智能 (AI) 和深度学习的自动化针点定位显示了改善传统针的前景. 本综述强调了人工智能驱动的针点识别的当前方法,局限性和未来方向.
科学领域:
- 综合医学是一个整体的医学.
- 医疗技术 医疗技术 医学技术
- 人工智能的人工智能
背景情况:
- 针是一种全球应用的传统疗法.
- 传统的针点定位依赖于主观的临床经验.
- 人工智能的进步,特别是深度学习,正在使自动化方法成为可能.
研究的目的:
- 通过使用传统算法和深度学习,系统地审查有关针点本地化的文献.
- 评估自动化针点定位技术的有效性和局限性.
- 确定基于人工智能的针点识别的未来研究方向.
主要方法:
- 对点局部化研究的系统文献综述.
- 分析传统的算法和深度学习方法.
- 对不同解剖区域的技术进行评估.
主要成果:
- 当前的人工智能和深度学习方法显示了自动化针点定位的潜力.
- 现有技术的局限性需要进一步的研究和开发.
- 该审查确定了未来调查的关键挑战和领域.
结论:
- 预计随着人工智能的进一步发展,自动化针点定位技术将得到改进.
- 克服当前的挑战将导致人工智能驱动的针点识别带来更有希望的结果.
- 这篇评论鼓励进一步探索用于针点定位的先进AI方法.
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