Application and considerations of artificial intelligence and neuroimaging in the study of brain effect mechanisms of acupuncture and moxibustion.
10.13703/j.0255-2930.20241124-0001
- Author:
Ruqi ZHANG
1
;
Yiding ZHAO
1
;
Shengchun WANG
2
Author Information
1. School of Acupuncture-Moxibustion and Tuina, Shandong University of TCM, Jinan 250014, China.
2. Department of Acupuncture-Moxibustion, Physiotherapy and Rehabilitation, Shandong Provincial Hospital Affiliated to First Medical University of Shandong, Jinan
- Publication Type:Journal Article
- Keywords:
acupuncture and moxibustion;
artificial intelligence (AI);
brain effect;
neuroimaging
- MeSH:
Humans;
Acupuncture Therapy;
Brain/physiology*;
Moxibustion;
Neuroimaging/methods*;
Artificial Intelligence;
Magnetic Resonance Imaging;
Electroencephalography
- From:
Chinese Acupuncture & Moxibustion
2025;45(4):428-434
- CountryChina
- Language:Chinese
-
Abstract:
Electroencephalography (EEG) and magnetic resonance imaging (MRI), as neuroimaging technologies, provided objective and visualized technical tools for analyzing the brain effect mechanisms of acupuncture and moxibustion from the perspectives of brain structure, function, metabolism, and hemodynamics. The advancement of artificial intelligence (AI) algorithms can compensate for issues such as the large and scattered nature of neuroimaging data, inconsistent quality, and high heterogeneity of image information. The integration of AI with neuroimaging can facilitate individualized, intelligent, and precise prediction of acupuncture and moxibustion effects, enable intelligent classification of differential acupuncture responses, and identify brain activation patterns. This paper focuses on EEG and MRI, analyzing how machine learning and deep learning optimize multimodal neuroimaging data and their applications in the study of acupuncture and moxibustion brain effects mechanisms. Furthermore, it highlights current research gaps and limitations to provide insights for future studies on acupuncture brain effects mechanisms.
