Application of Artificial Intelligence in Acupuncture Point Location and Prescription Optimization

Corresponding author: wanglong, 3157767144@qq.com

DOI: 10.12201/bmr.202508.00053

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  Abstract: In this paper, we review the application progress of artificial intelligence (AI) in acupoint localization and prescription optimization in acupuncture. Traditional manner of acupoint localization is limited by individual physiological differences and practitioner experience, which affects its accuracy. In the aspect of acupoint localization, AI-based deep learning algorithms, supplemented by sensor technology, can utilize human image data for precise localization. For prescription optimization, data mining techniques are employed to uncover therapeutic patterns of acupoints. Additionally, complex network analysis reveals the relationships among different acupoints, with large language models providing intelligent interaction. The article points out challenges in the field such as data quality, ethical privacy and clinical acceptance, and indicates the directions for development of AI technologies, promoting interdisciplinary integration of AI with various medical fields.

  Key words: Artificial; Intelligence, Deep; Learning, Acupuncture, Acupoint; Location, Prescription; Optimization.

  Submit time: 29 August 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  1	2025-07-14	bmr.202508.00053V1	Download

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