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[Exploration on the application characteristics of bloodletting therapy for the diseases relevant with soft tissue infection by data mining technology].

AbstractOBJECTIVE:
Using the data mining technology to analyze the application law of bloodletting therapy for the diseases relevant with soft tissue infection and explore the effect specificity of bloodletting therapy.
METHODS:
The variety of diseases treated with bloodletting therapy was taken as the sample data by collecting the reports from the periodical literatures. The network database of bloodletting literature was set up. The association rule of data mining technology was adopted to extract the information on the diseases relevant with soft tissue infection in the periodical literatures. The frequency item of the superiority disease category was calculated. And the deep mining was done in terms of the needle device, point selection and the bleeding amount separately. The application law of bloodletting therapy was summarized in the treatment of the diseases relevant with soft tissue infection.
RESULTS:
Fourteen kinds of relevant diseases of soft tissue infection treated with bloodletting therapy were included in the contemporary periodical literatures, of which, the reported case number and the reporting frequency were the highest for hordeolum and breast abscess. The three-edged needle was used the most frequently in the manipulation. The acupoints selected were the local Ashi points, combined with the symptomatic acupoints. The bleeding amount was not normalized by the ideas of different physicians.
CONCLUSION:
The bloodletting therapy achieves the better curative effect on some diseases relevant with soft tissue infection and this therapy deserves to be further promoted in clinical practice.
AuthorsYan-Hui Sun, Chun-Sheng Jia, Jian-Ling Wang, Wei-Juan Gang, Xiao-Feng Li, Xiao-Xu Zhang, Xin Liu, Yu-Zhu Du
JournalZhongguo zhen jiu = Chinese acupuncture & moxibustion (Zhongguo Zhen Jiu) Vol. 33 Issue 9 Pg. 803-7 (Sep 2013) ISSN: 0255-2930 [Print] China
PMID24298772 (Publication Type: English Abstract, Journal Article, Research Support, Non-U.S. Gov't)
Topics
  • Acupuncture Points
  • Bloodletting (instrumentation, methods)
  • Data Mining
  • Female
  • Humans
  • Soft Tissue Infections (therapy)

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