ArticlePLoS computational biology2019
Predicting Meridian in Chinese traditional medicine using machine learning approaches.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- FuTCM-PDD: a multi-level information fusion framework integrating KAN modeling and AutoML for phenotype-based drug discovery from Traditional Chinese Medicine.Chinese medicine · 2026Article
- Advancing the modernization of traditional Chinese medicine through artificial intelligence and multimodal data integration.Chinese medicine · 2026Review
- Development and application of artificial intelligence in traditional Chinese medicine research and development.Chinese medicine · 2026Review
- A review of recent artificial intelligence for traditional medicine.Journal of traditional and complementary medicine · 2025Review
- Computer-Aided Drug Design in Research on Chinese Materia Medica: Methods, Applications, Advantages, and Challenges.Pharmaceutics · 2025Review
- Understanding the molecular basis of herbal medicines for cough variant asthma under the guidance of traditional herbal theories.Frontiers in pharmacology · 2025Article
- Digital intelligence technology: new quality productivity for precision traditional Chinese medicine.Frontiers in pharmacology · 2025Review
- Active Targets and Potential Mechanisms of Erhuang Quzhi Formula in Treating NAFLD: Network Analysis and Experimental Assessment.Cell biochemistry and biophysics · 2024Article
- Mechanism of Artemisia annua L. in the treatment of acute myocardial infarction: network pharmacology, molecular docking and in vivo validation.Molecular diversity · 2024Article
- Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study.Briefings in bioinformatics · 2024Article
- Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare.Integrative medicine research · 2024Article
- Infrared Imageries of Human Body Activated by Tea Match the Hypothesis of Meridian System.Phenomics (Cham, Switzerland) · 2023Article
- Machine learning in TCM with natural products and molecules: current status and future perspectives.Chinese medicine · 2023Review
- Machine Learning Applications in Drug Repurposing.Interdisciplinary sciences, computational life sciences · 2022Review
- IrGO: Iranian traditional medicine General Ontology and knowledge base.Journal of biomedical semantics · 2021Article
- Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning.Chinese medicine · 2021Article
- Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products.Frontiers in chemistry · 2021Review
- Efficacy and Safety of Lianhuaqingwen Capsules for the Prevention of Coronavirus Disease 2019: A Prospective Open-Label Controlled Trial.Evidence-based complementary and alternative medicine : eCAM · 2021Article
- Antibacterial Activity Prediction Model of Traditional Chinese Medicine Based on Combined Data-Driven Approach and Machine Learning Algorithm: Constructed and Validated.Frontiers in microbiology · 2021Article
- Practical Implementation of Artificial Intelligence-Based Deep Learning and Cloud Computing on the Application of Traditional Medicine and Western Medicine in the Diagnosis and Treatment of Rheumatoid Arthritis.Frontiers in pharmacology · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Plant-derived nature products, known as herb formulas, have been commonly used in Traditional Chinese Medicine (TCM) for disease prevention and treatment. The herbs have been traditionally classified into different categories according to the TCM Organ systems known as Meridians. Despite the increasing knowledge on the active components of the herbs, the rationale of Meridian classification remains poorly understood. In this study, we took a machine learning approach to explore the classification of Meridian. We determined the molecule features for 646 herbs and their active components including structure-based fingerprints and ADME properties (absorption, distribution, metabolism and excretion), and found that the Meridian can be predicted by machine learning approaches with a top accuracy of 0.83. We also identified the top compound features that were important for the Meridian prediction. To the best of our knowledge, this is the first time that molecular properties of the herb compounds are associated with the TCM Meridians. Taken together, the machine learning approach may provide novel insights for the understanding of molecular evidence of Meridians in TCM.
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