Artificial intelligence (AI) is increasingly applied in clinical acupuncture to modernize diagnosis and treatment. By addressing critical gaps in traditional practice, such as the lack of objective standardization in acupoint selection, reliance on subjective practitioner experience for localization, insufficient real-time safety monitoring, and the need for personalized efficacy prediction—AI offers significant clinical value. This paper reviews the application of AI in acupuncture across these four key areas. We summarize existing research and provide recommendations to guide the future development of intelligent acupuncture systems.
Nie et al. (Mon,) studied this question.
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