<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Acupuncture and moxibustion are increasingly recognized as effective and safe modalities for the management of neurological disorders, garnering substantial interest from both neurologists and patients. This study systematically reviews literature from major databases spanning the years 2012 to 2024 to construct a comprehensive dataset on the acupuncture treatment of neurological diseases. The data were meticulously compiled through a detailed search and screening process, adhering to established principles for data extraction and segmentation. The resultant acupuncture treatment database served as the foundation for subsequent analyses utilizing the association rule algorithm. This advanced computational approach facilitated a deep investigation into the relationships among acupuncture points used in neurological treatments. By employing a complex network analysis, the study identified the optimal distribution of acupuncture points, and cluster analysis further categorized these points for diverse neurological conditions. Our findings indicate that a total of 206 acupuncture points are prevalently used in neurological therapies. The regions of the head, face, and neck are most frequently targeted, with these areas collectively accounting for 1,048 instances of point utilization. Specifically, 124 unique acupuncture points have been identified as particularly effective for neurological applications. The association pairs “Yangbai-Zusanli” and “Sanyinjiao-Zusanli” demonstrated the highest levels of support and confidence, at 96.29% and 48.59% respectively. The core constellation of acupuncture points, comprising “Zhuzhu,” “Yangbai,” “Sizhukong,” “Yuyin,” “Sibai,” “Zusanli,” and “Baihui,” encapsulates the strategic focal areas for enhancing therapeutic outcomes in neurology. The integration of data mining techniques in this research not only underscores the specific patterns in the distribution of acupuncture points but also suggests a potential framework for augmenting the efficacy of treatments for neurological conditions. Through such analytical methodologies, the study contributes to a nuanced understanding of acupuncture’s role in neurology, paving the way for targeted and optimized therapeutic strategies.</p>
</abstract>

Acupuncture and moxibustion are increasingly recognized as effective and safe modalities for the management of neurological disorders, garnering substantial interest from both neurologists and patients. This study systematically reviews literature from major databases spanning the years 2012 to 2024 to construct a comprehensive dataset on the acupuncture treatment of neurological diseases. The data were meticulously compiled through a detailed search and screening process, adhering to established principles for data extraction and segmentation. The resultant acupuncture treatment database served as the foundation for subsequent analyses utilizing the association rule algorithm. This advanced computational approach facilitated a deep investigation into the relationships among acupuncture points used in neurological treatments. By employing a complex network analysis, the study identified the optimal distribution of acupuncture points, and cluster analysis further categorized these points for diverse neurological conditions. Our findings indicate that a total of 206 acupuncture points are prevalently used in neurological therapies. The regions of the head, face, and neck are most frequently targeted, with these areas collectively accounting for 1,048 instances of point utilization. Specifically, 124 unique acupuncture points have been identified as particularly effective for neurological applications. The association pairs “Yangbai-Zusanli” and “Sanyinjiao-Zusanli” demonstrated the highest levels of support and confidence, at 96.29% and 48.59% respectively. The core constellation of acupuncture points, comprising “Zhuzhu,” “Yangbai,” “Sizhukong,” “Yuyin,” “Sibai,” “Zusanli,” and “Baihui,” encapsulates the strategic focal areas for enhancing therapeutic outcomes in neurology. The integration of data mining techniques in this research not only underscores the specific patterns in the distribution of acupuncture points but also suggests a potential framework for augmenting the efficacy of treatments for neurological conditions. Through such analytical methodologies, the study contributes to a nuanced understanding of acupuncture’s role in neurology, paving the way for targeted and optimized therapeutic strategies.

Study on the law of acupuncture treatment in neurology based on data mining technology

College of Acupuncture and Massage, Changchun University of Chinese Medicine

Jilin Engineering Vocational College, Siping

College of Basic Medicine, Changchun University of Chinese Medicine, Changchun

College of Traditional Chinese Medicine, Changchun University of Chinese Medicine

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Acupuncture and moxibustion are increasingly recognized as effective and safe modalities for the management of neurological disorders, garnering substantial...

Study on the law of acupuncture treatment in neurology based on data mining technology

Publié en ligne: 05 août 2024

Pages: -

Reçu: 05 avr. 2024

Accepté: 30 juin 2024

DOI: https://doi.org/10.2478/amns-2024-2010

Mots clés
Association rules, Complex networks, Cluster analysis, Acupuncture, Neurology

© 2024 Shuo Yu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Study on the law of acupuncture treatment in neurology based on data mining technology

Publié en ligne: 05 août 2024

Pages: -

Reçu: 05 avr. 2024

Accepté: 30 juin 2024

DOI: https://doi.org/10.2478/amns-2024-2010

Mots clésAssociation rules, Complex networks, Cluster analysis, Acupuncture, Neurology

© 2024 Shuo Yu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Association rules, Complex networks, Cluster analysis, Acupuncture, Neurology