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Construction Strategy of Machine Learning-Based Individualized Syndrome Differentiation Model and Intelligent Diagnosis-Treatment Framework in Traditional Chinese Medicine
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Xinning QU, Hongxiao LIU
Chinese Archives of Traditional Chinese Medicine | 2026, 44(8) : 19 - 22
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Chinese Archives of Traditional Chinese Medicine | 2026, 44(8): 19-22
• Digital Traditional Chinese Medicine •
Construction Strategy of Machine Learning-Based Individualized Syndrome Differentiation Model and Intelligent Diagnosis-Treatment Framework in Traditional Chinese Medicine
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Xinning QU, Hongxiao LIU
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  • Guang'anmen Hospital China Academy of Chinese Medical Sciences, Beijing 100053, China
Published: 2026-08-10 doi: 10.13193/j.issn.1673-7717.2026.08.004
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Macroscopic syndrome differentiation is the foundation of the traditional Chinese medicine (TCM) diagnosis and treatment system. Through the four diagnostic methods of observation, auscultation and olfaction, inquiry and palpation, it integrates and analyzes the overall state of the patient and the characteristics of the disease, “understanding the interior from the exterior” and “diagnosing the interior from the exterior”, thus forming an overall understanding of the pathogenesis. Microscopic syndrome differentiation, by detecting microscopic indicators such as the tissue, cell, molecular and genetic levels of the patients, revealed the deep mechanism and material basis of syndromes. It is a supplement to macroscopic syndrome differentiation and also an important direction for the precision of traditional Chinese medicine. This paper reviewed the current research status of the objectification of TCM syndromes from the perspectives of macro and micro syndrome differentiation respectively. It proposed to establish a “macro-micro” feature correlation model through machine learning, systematically drew the knowledge graph of TCM “syndromes” and on this basis, sequentially collected disease characteristic information, accurately grasped the changes and development trends of syndromes and form clinical sequential diagnosis and treatment auxiliary decision-making. It is an effective path for traditional Chinese medicine to move towards precision medicine.

machine learning  /  individualized diagnosis and treatment  /  intelligent diagnosis and treatment  /  macroscopic diagnosis and treatment  /  microscopic diagnosis and treatment
屈馨宁, 刘宏潇. 基于机器学习的中医个体化辨证模式及智慧诊疗模型构建思路. 中华中医药学刊, 2026 , 44 (8) : 19 -22 . DOI: 10.13193/j.issn.1673-7717.2026.08.004
Xinning QU, Hongxiao LIU. Construction Strategy of Machine Learning-Based Individualized Syndrome Differentiation Model and Intelligent Diagnosis-Treatment Framework in Traditional Chinese Medicine[J]. Chinese Archives of Traditional Chinese Medicine, 2026 , 44 (8) : 19 -22 . DOI: 10.13193/j.issn.1673-7717.2026.08.004
Year 2026 volume 44 Issue 8
91
11
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doi: 10.13193/j.issn.1673-7717.2026.08.004
  • Online Date:2026-10-20
  • Published:2026-08-10
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    Guang'anmen Hospital China Academy of Chinese Medical Sciences, Beijing 100053, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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