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Data Mining-based Analysis of Acupoint Selection Patterns for Chronic Hepatitis B Infection

  • Yan Yang1,
  • Fei-Lin Ge2,
  • Jun-Yuan Deng1,
  • Yun-Hao Yang1,
  • Chen Luo1 and
  • Cheng-Lin Tang1,*
 Author information 

Abstract

Background

The purpose of this study was to identify the characteristics and principles of acupoints applied for treating chronic hepatitis B infection.

Methods

The published clinical studies on acupuncture for the treatment of chronic hepatitis B infection were gathered from various databases, including SinoMed, Chongqing Vip, China National Knowledge Infrastructure, Wanfang, the Cochrane Library, PubMed, Web of Science and Embase. Excel 2019 was utilized to establish a database of acupuncture prescriptions and conduct statistics on the frequency, meridian application, distribution and specific points, as well as SPSS Modeler 18.0 and SPSS Statistics 26.0 to conduct association rule analysis and cluster analysis to investigate the characteristics and patterns of acupoint selection.

Results

A total of 42 studies containing 47 acupoints were included, with a total frequency of 286 acupoints. The top five acupoints used were Zusanli (ST36), Ganshu (BL18), Yanglingquan (GB34), Sanyinjiao (SP6) and Taichong (LR3), and the most commonly used meridians was the Bladder Meridian of Foot-Taiyang. The majority of acupuncture points are located in the lower limbs, back, and lumbar regions, with a significant percentage of them being Five-Shu acupoints. The strongest acupoint combination identified was Zusanli (ST36)–Ganshu (BL18), in addition to which 13 association rules and 4 valid clusters were obtained.

Conclusion

Zusanli (ST36)–Ganshu (BL18) could be considered a relatively reasonable prescription for treating chronic hepatitis B infection in clinical practice. However, further high-quality studies are needed.

Keywords

acupuncture therapy, chronic hepatitis B, data mining, association rule, cluster analysis

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Yang Y, Ge FL, Deng JY, Yang YH, Luo C, Tang CL. Data Mining-based Analysis of Acupoint Selection Patterns for Chronic Hepatitis B Infection. Gastroenterol & Hepatol Res. 2023;5(4):17. doi: 10.53388/ghr2023-03-081.
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Article History
Received Revised Accepted Published
December 29, 2023
DOI http://dx.doi.org/10.53388/ghr2023-03-081
  • Gastroenterology & Hepatology Research
  • eISSN 2703-173X
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Data Mining-based Analysis of Acupoint Selection Patterns for Chronic Hepatitis B Infection

Yan Yang, Fei-Lin Ge, Jun-Yuan Deng, Yun-Hao Yang, Chen Luo, Cheng-Lin Tang
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