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Theoretical Research of Deep Learning in Integrated Set Mode of Objective Data of Traditional Chinese Medicine Four Diagnoses
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Jiawei GENG1, 2, Yu TIAN1, 2, Shuyi WANG1, 2, Yunxuan DENG3, Jie YANG1, 2
Chinese Archives of Traditional Chinese Medicine | 2025, 43(11) : 21 - 27
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Chinese Archives of Traditional Chinese Medicine | 2025, 43(11): 21-27
• Digital Traditional Chinese Medicine •
Theoretical Research of Deep Learning in Integrated Set Mode of Objective Data of Traditional Chinese Medicine Four Diagnoses
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Jiawei GENG1, 2, Yu TIAN1, 2, Shuyi WANG1, 2, Yunxuan DENG3, Jie YANG1, 2
Affiliations
  • 1.Institute of Information on Traditional Chinese Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China
  • 2.National Data Center,China Academy of Chinese Medical Sciences,Beijing 100700,China
  • 3.College of Agricultural and Environmental Sciences,University of California,Davis 95616,USA
Published: 2025-11-10 doi: 10.13193/j.issn.1673-7717.2025.11.005
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This paper gave a detailed introduction to the application advantages and future development of deep learning in the objectification of the four diagnoses of traditional Chinese medicine,and explored the establishment of a new data integration collection processing idea based on deep learning in the objectification of the four diagnoses of traditional Chinese medicine. This paper summarized the research background of deep learning in the objectification of the four diagnoses of traditional Chinese medicine and the deep learning methods commonly used in the objectification of the four diagnoses of traditional Chinese medicine,and introduced the specific applications of deep learning in the objectification of the four diagnoses of traditional Chinese medicine in detail. The applications in inspection are divided into tongue diagnosis and face diagnosis,including tongue image data processing,tongue image data analysis,and face diagnosis data collection and analysis. In listening and smelling diagnosis,it is divided into the application of sound diagnosis and sniff diagnosis. It can be divided into the application of medical recommendation model and auxiliary diagnosis model. It is divided into the application of signal recognition and pulse classification,and the application of deep learning in traditional Chinese medicine diagnosis model and service platform,and discussed the application advantages and future prospects of deep learning in the objectification of traditional Chinese medicine four diagnoses. Based on deep learning,the integrated collection mode of objective data of the four diagnoses of traditional Chinese medicine is to classify the collected original four diagnoses data into the corresponding four diagnoses database after deep learning processing,and then output feedback with the exchange platform,and finally classify and apply.

deep learning  /  artificial intelligence  /  objectification of four diagnoses of traditional Chinese medicine  /  data mining  /  convolutional neural network
耿嘉蔚, 田雨, 王舒怡, 邓云轩, 杨杰. 深度学习在中医四诊客观数据一体化集合模式的理论研究. 中华中医药学刊, 2025 , 43 (11) : 21 -27 . DOI: 10.13193/j.issn.1673-7717.2025.11.005
Jiawei GENG, Yu TIAN, Shuyi WANG, Yunxuan DENG, Jie YANG. Theoretical Research of Deep Learning in Integrated Set Mode of Objective Data of Traditional Chinese Medicine Four Diagnoses[J]. Chinese Archives of Traditional Chinese Medicine, 2025 , 43 (11) : 21 -27 . DOI: 10.13193/j.issn.1673-7717.2025.11.005
Year 2025 volume 43 Issue 11
49
20
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doi: 10.13193/j.issn.1673-7717.2025.11.005
  • Online Date:2026-10-30
  • Published:2025-11-10
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    1.Institute of Information on Traditional Chinese Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China
    2.National Data Center,China Academy of Chinese Medical Sciences,Beijing 100700,China
    3.College of Agricultural and Environmental Sciences,University of California,Davis 95616,USA
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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
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Percentage of
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Genus
种数
Number of
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Percentage of total
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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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