ArticleEvidence-based complementary and alternative medicine : eCAM2021
An Apriori Algorithm-Based Association Rule Analysis to Identify Acupoint Combinations for Treating Diabetic Gastroparesis.
Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Exploring psychological symptom associations among people living with HIV using an apriori algorithm.BMC infectious diseases · 2026Article
- Study protocol for a prospective, investigator-initiated clinical trial on the vascular effects of acupuncture in the abdomen and lower limbs for patients with diarrhea-predominant irritable bowel syndrome.International journal of colorectal disease · 2025Article
- Exploring the potential of acupuncture practice education using artificial intelligence.Integrative medicine research · 2025Review
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- Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Piriformis Syndrome: A Protocol for Data Mining.Journal of pain research · 2023Article
- A novel FCTF evaluation and prediction model for food efficacy based on association rule mining.Frontiers in nutrition · 2023Article
- Artificial intelligence-directed acupuncture: a review.Chinese medicine · 2022Review
- Analysis of Acupoints Combination for Cancer-Related Anorexia Based on Association Rule Mining.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Combined Acupoints for the Treatment of Patients with Obesity: An Association Rule Analysis.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Sports Medical Image Modeling of Injury Prevention in Dance Learning and Sports Training.Scanning · 2022Article
- An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain.Frontiers in pain research (Lausanne, Switzerland) · 2022Article
- Enterprise Operating State Evaluation Based on Association Rule Algorithm and Data Set.Computational intelligence and neuroscience · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.