ArticleChinese medicine2021
Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning.
Article in Chinese medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Study on diagnostic models for insomnia and gastralgia with Liver-Spleen Disharmony Syndrome based on machine learning.Frontiers in medicine · 2026Article
- A supported decision-making model for idiopathic pulmonary fibrosis based on feature screening and optimized neural network.Scientific reports · 2025Article
- Study on subtyping and Traditional Chinese Medicine treatment of depression based on machine learning and text mining.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2025Article
- The integration of machine learning into traditional Chinese medicine.Journal of pharmaceutical analysis · 2025Review
- A review of recent artificial intelligence for traditional medicine.Journal of traditional and complementary medicine · 2025Review
- Insomnia treatment based on the regulation of the GABAergic system: traditional Chinese medicine perspectives and therapeutic approaches.Frontiers in neuroscience · 2025Review
- Explainable machine learning model and nomogram for predicting the efficacy of Traditional Chinese Medicine in treating Long COVID: a retrospective study.Frontiers in medicine · 2025Article
- Digital intelligence technology: new quality productivity for precision traditional Chinese medicine.Frontiers in pharmacology · 2025Review
- KGSD-Net: a knowledge graph syndrome differentiation network for syndrome classification.Frontiers in medicine · 2025Article
- Research progress on the effect of medicine and food homology resources for sleep improvement.Heliyon · 2024Review
- G protein-coupled receptors and traditional Chinese medicine: new thinks for the development of traditional Chinese medicine.Chinese medicine · 2024Review
- Machine Learning Research Trends in Traditional Chinese Medicine: A Bibliometric Review.International journal of general medicine · 2024Review
- Research progress in the prevention and treatment of insomnia with classical prescriptions.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023Article
- Acupuncture at Back-Shu point improves insomnia by reducing inflammation and inhibiting the ERK/NF-κB signaling pathway.World journal of psychiatry · 2023Article
- Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review.Frontiers in pharmacology · 2023Review
- Multi-Task Joint Learning Model for Chinese Word Segmentation and Syndrome Differentiation in Traditional Chinese Medicine.International journal of environmental research and public health · 2022Article
- Proteomics Reveals Molecular Changes in Insomnia Patients with More Dreams.Computational and mathematical methods in medicine · 2022Article
- Syndrome Differentiation and Treatment Regularity in Traditional Chinese Medicine for Type 2 Diabetes: A Text Mining Analysis.Frontiers in endocrinology · 2021Review
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7 authors.
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Abstract
backgroundInsomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning.
methodsFirst of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest.
resultsResearches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combinations of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment.
conclusionsThe results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.
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