ArticleJournal of clinical medicine2019
Revealing Associations between Diagnosis Patterns and Acupoint Prescriptions Using Medical Data Extracted from Case Reports.
Article in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Discovering the key symptoms for identifying patterns in functional dyspepsia patients: Doctor's decision and machine learning.Integrative medicine research · 2025Article
- Performance of GPT-4 for planning acupuncture treatment: comparison with human clinician performance.Frontiers in medicine · 2025Article
- Identifying Key Node with Motif-Based PageRank on Acupoint-Disease Network.Evidence-based complementary and alternative medicine : eCAM · 2023Article
- Deep autoencoder-powered pattern identification of sleep disturbance using multi-site cross-sectional survey data.Frontiers in medicine · 2022Article
- Application of Virtual Reality Technology in Clinical Practice, Teaching, and Research in Complementary and Alternative Medicine.Evidence-based complementary and alternative medicine : eCAM · 2022Review
- Diversity of Acupuncture Point Selections According to the Acupuncture Styles and Their Relations to Theoretical Elements in Traditional Asian Medicine: A Data-Mining-Based Literature Study.Journal of clinical medicine · 2021Article
- Identification of Acupoint Indication from Reverse Inference: Data Mining of Randomized Controlled Clinical Trials.Journal of clinical medicine · 2020Article
- Acupoint selection based on pattern identification results or disease state.Integrative medicine research · 2020Article
- Statistical inference of acupoint specificity: forward and reverse inference.Integrative medicine research · 2020Article
- Commonality and Specificity of Acupuncture Point Selections.Evidence-based complementary and alternative medicine : eCAM · 2020Article
- A Key Node Mining Method Based on Acupoint-Disease Network (ADN): A New Perspective for Exploring Acupoint Specificity.Evidence-based complementary and alternative medicine : eCAM · 2020Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveThe optimal acupoints for a particular disease can be determined by analysis of diagnosis patterns. The objective of this study was to reveal the association between such patterns and the acupoints prescribed in clinical practice using medical data extracted from case reports.
methodsThis study evaluated online virtual diagnoses made by currently practicing Korean medical doctors (N = 80). The doctors were presented with 10 case reports published in Korean medical journals and were asked to diagnose the patients and prescribe acupoints accordingly. A network analysis and the term frequency-inverse document frequency (tf-idf) method were used to analyse and quantify the relationship between diagnosis patterns and prescribed acupoints.
resultsThe network analysis showed that ST36, LI4, LR3, and SP6 were the most frequently used acupoints across all diagnoses. The tf-idf values showed the acupoints used for specific diseases, such as BL40 for bladder disease and LU9 for lung disease.
conclusionsThe associations between diagnosis patterns and prescribed acupoints were identified using an online virtual diagnosis modality. Network and text mining analyses revealed commonly applied and disease-specific acupoints in both qualitative and quantitative terms.
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