ArticleFrontiers in pharmacology2020
Application of Neural Network and Cluster Analyses to Differentiate TCM Patterns in Patients With Breast Cancer.
Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 25 citations in OpenAlex.
- A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation.JMIR medical informatics · 2025Article
- Discovering the key symptoms for identifying patterns in functional dyspepsia patients: Doctor's decision and machine learning.Integrative medicine research · 2025Article
- Predicting TCM patterns in PCOS patients: An exploration of feature selection methods and multi-label machine learning models.Heliyon · 2024Article
- A Systematic Review of Application Progress on Machine Learning-Based Natural Language Processing in Breast Cancer over the Past 5 Years.Diagnostics (Basel, Switzerland) · 2023Review
- Analysis of Traditional Chinese Medicine Symptoms in Children with Spastic Cerebral Palsy, a Protocol for Data Mining.Journal of multidisciplinary healthcare · 2023Article
- A Traditional Chinese Medicine Syndrome Classification Model Based on Cross-Feature Generation by Convolution Neural Network: Model Development and Validation.JMIR medical informatics · 2022Article
- Deep autoencoder-powered pattern identification of sleep disturbance using multi-site cross-sectional survey data.Frontiers in medicine · 2022Article
- Chinese Medicine Syndrome Differentiation for Early Breast Cancer: A Multicenter Prospective Clinical Study.Frontiers in oncology · 2022Article
- The Research and Development Thinking on the Status of Artificial Intelligence in Traditional Chinese Medicine.Evidence-based complementary and alternative medicine : eCAM · 2022Review
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposePattern differentiation is a critical element of the prescription process for Traditional Chinese Medicine (TCM) practitioners. Application of advanced machine learning techniques will enhance the effectiveness of TCM in clinical practice. The aim of this study is to explore the relationships between clinical features and TCM patterns in breast cancer patients.
methodsThe dataset of breast cancer patients receiving TCM treatment was recruited from a single medical center. We utilized a neural network model to standardize terminologies and address TCM pattern differentiation in breast cancer cases. Cluster analysis was applied to classify the clinical features in the breast cancer patient dataset. To evaluate the performance of the proposed method, we further compared the TCM patterns to therapeutic principles of Chinese herbal medication in Taiwan.
resultsA total of 2,738 breast cancer cases were recruited and standardized. They were divided into 5 groups according to clinical features
conclusionThis is the first study using machine-learning methodology to standardize and analyze TCM electronic medical records. The patterns revealed by the analyses were highly correlated with the therapeutic principles of TCM practitioners. Machine learning technology could assist TCM practitioners to comprehensively differentiate patterns and identify effective Chinese herbal medicine treatments in clinical practice.
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