Dataset Information

An Apriori Algorithm-Based Association Rule Analysis to Identify Acupoint Combinations for Treating Diabetic Gastroparesis.

ABSTRACT: We explored the potential association rules within acupoints in treating diabetic gastroparesis (DGP) using Apriori algorithm complemented with another partition-based algorithm, a frequent pattern growth algorithm. Apriori algorithm is a data mining-based analysis that is widely applied in various fields, such as business and medicine, to mine frequent patterns in datasets. To search for effective acupoint combinations in the treatment of DGP, we implemented Apriori algorithm to investigate the association rules of acupoints among 17 randomized controlled trials (RCTs). The acupoints were extracted from the 17 included RCTs. In total, 29 distinct acupoints were observed in the RCTs. The top 10 frequently selected acupoints were CV12, ST36, PC6, ST25, BL21, BL20, BL23, SP6, BL18, and ST21. The frequency pattern of acupoints achieved by using a frequent pattern growth algorithm also confirms the result. The results showed that the most associated rules were {BL23, BL18} ≥ {SP6}, {BL20, BL18} ≥ {PC6}, {PC6, BL18} ≥ {BL20}, and {SP6, BL18} ≥ {BL23} in the database. Acupoints, including BL23, BL18, SP6, BL20, and PC6, can be deemed as core elements of acupoint combinations for treating DGP.

SUBMITTER: Lu PH

PROVIDER: S-EPMC8018850 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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An Apriori Algorithm-Based Association Rule Analysis to Identify Acupoint Combinations for Treating Diabetic Gastroparesis.

Lu Ping-Hsun PH Keng Jui-Lin JL Tsai Fu-Ming FM Lu Po-Hsuan PH Kuo Chan-Yen CY

Evidence-based complementary and alternative medicine : eCAM 20210325

We explored the potential association rules within acupoints in treating diabetic gastroparesis (DGP) using Apriori algorithm complemented with another partition-based algorithm, a frequent pattern growth algorithm. Apriori algorithm is a data mining-based analysis that is widely applied in various fields, such as business and medicine, to mine frequent patterns in datasets. To search for effective acupoint combinations in the treatment of DGP, we implemented Apriori algorithm to investigate the ...[more]

PMID: 33833818

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Project description:Since water supply association analysis plays an important role in attribution analysis of water supply fluctuation, how to carry out effective association analysis has become a critical problem. However, the current techniques and methods used for association analysis are not very effective because they are based on continuous data. In general, there is different degrees of monotone relationship between continuous data, which makes the analysis results easily affected by monotone relationship. The multicollinearity between continuous data distorts these analytical methods and may generate incorrect results. Meanwhile, we cannot know the association rules and value interval between features and water supply. Therefore, the lack of an effective analysis method hinders the water supply association analysis. Association rules and value interval of features obtained from association analysis are helpful to grasp cause of water supply fluctuation and know the fluctuation interval of water supply, so as to provide better support for water supply dispatching. But the association rules and value interval between features and water supply are not fully understood. In this study, a data mining method coupling kmeans clustering discretization and apriori algorithm was proposed. The kmeans was used for data discretization to obtain the one-hot encoding that can be recognized by apriori, and the discretization can also avoid the influence of monotone relationship and multicollinearity on analysis results. All the rules eventually need to be validated in order to filter out spurious rules. The results show that the method in this study is an effective association analysis method. The method can not only obtain the valid strong association rules between features and water supply, but also understand whether the association relationship between features and water supply is direct or indirect. Meanwhile, the method can also obtain value interval of features, the association degree between features and confidence probability of rules.

Project description:Macrophage-based immune dysregulation plays a critical role in development of delayed gastric emptying in diabetic mice. Loss of anti-inflammatory macrophages and increased expression of genes associated with pro-inflammatory macrophages has been reported in full-thickness gastric biopsies from gastroparesis patients. We aimed to determine broader protein expression (proteomics) and protein-based signaling pathways in gastric biopsies of diabetic (DG) and idiopathic gastroparesis (IG) patients. Additionally, we determined correlations between protein expressions, gastric emptying, and symptoms. Full-thickness gastric antrum biopsies were obtained from nine DG patients, seven IG patients, and five nondiabetic controls. Aptamer-based SomaLogic tissue scan that quantitatively identifies 1,305 human proteins was used. Protein fold changes were computed, and differential expressions were calculated using Limma. Ingenuity pathway analysis and correlations were carried out. Multiple-testing corrected P < 0.05 was considered statistically significant. Seventy-three proteins were differentially expressed in DG, 132 proteins were differentially expressed in IG, and 40 proteins were common to DG and IG. In both DG and IG, "Role of Macrophages, Fibroblasts and Endothelial Cells" was the most statistically significant altered pathway [DG false discovery rate (FDR) = 7.9 × 10-9; IG FDR = 6.3 × 10-12]. In DG, properdin expression correlated with GCSI bloating (r = -0.99, FDR = 0.02) and expressions of prostaglandin G/H synthase 2, protein kinase C-ζ type, and complement C2 correlated with 4 h gastric retention (r = -0.97, FDR = 0.03 for all). No correlations were found between proteins and symptoms or gastric emptying in IG. Protein expression changes suggest a central role of macrophage-driven immune dysregulation in gastroparesis, specifically, complement activation in diabetic gastroparesis.NEW & NOTEWORTHY This study uses SOMAscan, a novel proteomics assay for determination of altered proteins and associated molecular pathways in human gastroparesis. Seventy-three proteins were changed in diabetic gastroparesis, 132 in idiopathic gastroparesis compared with controls. Forty proteins were common in both. Macrophage-based immune dysregulation pathway was most significantly affected in both diabetic and idiopathic gastroparesis. Proteins involved in the complement and prostaglandin synthesis pathway were associated with symptoms and gastric emptying delay in diabetic gastroparesis.

Dataset Information

An Apriori Algorithm-Based Association Rule Analysis to Identify Acupoint Combinations for Treating Diabetic Gastroparesis.

Publications

An Apriori Algorithm-Based Association Rule Analysis to Identify Acupoint Combinations for Treating Diabetic Gastroparesis.

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