scholarly journals An Association Rule Analysis of Acupressure Effect on Sleep Quality

Author(s):  
Chih-Hung Lin ◽  
I-Shiang Tzeng ◽  
Ya-Hsuan Lin ◽  
Chan-Yen Kuo
2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Chih-Hung Lin ◽  
Ya-Hsuan Lin ◽  
I-Shiang Tzeng ◽  
Chan-Yen Kuo

Background. Sleep is recognized as an all-important physiological process, which also contributes to maintaining several bodily functions and systems. According to the Pittsburgh Sleep Quality Index (PSQI), also known as the most widely used tool in the field of subjective assessment of self-perceived sleep quality, a combination of acupoints could be more effective than single acupoint treatment in improving sleep quality. Methods. The present study was based on the extracted eligible studies rooted in a previous meta-analysis that worked on the basis of association rule mining and examined the potential kernel acupoint combinations for improving sleep quality. Results. Depending on the Apriori algorithm, we summarized 26 acupoints as binary data from the 32 eligible studies based on a previous meta-analysis and analyzed them. The top 10 most frequently selected acupoints were HT7, SP6, PC6, KI1, GV20, EM5, EX-HN3, EX-HN16, KI3, and MA-TF1. Furthermore, as deduced from 21 association rules, the primary relevant rules in the combination of acupoints are (EX-HN3, EX-HN16)=>(GV20) and (HT7, KI1)=>(PC6). Conclusions. In order to use acupuncture to improve sleep quality, integrating (EX-HN3, EX-HN16, GV20) with (HT7, KI1, PC6) acupoints could be deemed as the kernel acupoint combination.


Author(s):  
Qian Gao ◽  
Chenglong Liu ◽  
Yishun Li ◽  
Yuchuan Du ◽  
Guanghua Yue ◽  
...  

2021 ◽  
Author(s):  
Linjiang Nan ◽  
Mingxiang Yang ◽  
Jianqiu Li ◽  
Ningpeng Dong ◽  
Hejia Wang

Author(s):  
Jing He ◽  
Yanchun Zhang ◽  
Guangyan Huang ◽  
Yefei Xin ◽  
Xiaohui Liu ◽  
...  

2016 ◽  
Vol 17 (1) ◽  
pp. 89 ◽  
Author(s):  
Elham Akhondzadeh Noughabi ◽  
Mohammad Reza Amin Naseri ◽  
Amir Albadvi ◽  
Mohammad Saeedi

2012 ◽  
Vol 66 (10) ◽  
pp. 2090-2098 ◽  
Author(s):  
Chi Zhang ◽  
Yilun Wang ◽  
Lili Zhang ◽  
Huicheng Zhou

In this paper, a computationally efficient version of the widely used Takagi-Sugeno (T-S) fuzzy reasoning method is proposed, and applied to river flood forecasting. It is well known that the number of fuzzy rules of traditional fuzzy reasoning methods exponentially increases as the number of input parameters increases, often causing prohibitive computational burden. The proposed method greatly reduces the number of fuzzy rules by making use of the association rule analysis on historical data, and therefore achieves computational efficiency for the cases of a large number of input parameters. In the end, we apply this new method to a case study of river flood forecasting, which demonstrates that the proposed fuzzy reasoning engine can achieve better prediction accuracy than the widely used Muskingum–Cunge scheme.


Author(s):  
H. Fang ◽  
C. Chen ◽  
J. Lin ◽  
X. Liu ◽  
D. Fang

The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP), where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality.


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